JP2019521398A - Adaptive audio codec system, method and medium - Google Patents

Abstract

The encoder includes a low pass filter that filters the input audio signal. The low pass filter has a fixed filter coefficient. The encoder generates a quantized signal based on the difference signal. The encoder includes an adaptive quantizer and a decoder that generates a feedback signal. The decoder has an inverse quantizer and a predictor. The predictor has a fixed control parameter based on the frequency response of the low pass filter. The predictor may include a finite impulse response filter with fixed filter coefficients. The decoder may include an adaptive noise shaping filter coupled between the low pass filter and the encoder. The adaptive noise shaping filter flattens the signal in the frequency spectrum corresponding to the frequency spectrum of the low pass filter. [Selection] Figure 1

Description

Cross-reference to related applications

  This patent application is entitled All Adaptive Audio Codec System, Method and Article, all filed May 10, 2016, US Patent Application No. 15 / 151,109, US Patent Application No. 15 No. 15 / 151,200, U.S. Patent Application No. 15 / 151,211, and U.S. Patent Application No. 15 / 151,220, which are incorporated herein by reference.

  This description relates to systems, methods, and articles for encoding and decoding audio signals.

  Differential pulse code modulation (DPCM) can be used to reduce the noise level or bit rate of the audio signal. The difference between the input audio signal and the prediction signal can be quantized to produce an output coded data stream of reduced energy. The prediction signal of the encoder can be generated using a decoder that includes an inverse quantizer and a predictor circuit. Adaptive differential pulse code modulation (ADPCM) changes the size of the quantizer steps of the quantizer (and dequantizer) to increase efficiency in terms of fluctuations in the dynamic range of the input signal.

In one embodiment, the apparatus is configured to generate a quantized signal based on the difference signal and a low pass filter having the determined filter coefficients and configured to filter the input signal, and adaptive A control circuit comprising an encoder having a quantizer and a decoder configured to generate a feedback signal and having an inverse quantizer and a predictor circuit, the predictor circuit being determined based on the frequency response of the low pass filter It has parameters. In one embodiment, the determined filter coefficients of the low pass filter are fixed filter coefficients of the low pass filter, the predictor circuit comprises a finite impulse response (FIR) filter, and the determined control parameters of the predictor circuit are FIR Contains the fixed filter coefficients of the filter. In one embodiment, the apparatus includes an adaptive noise shaping filter coupled between the low pass filter and the encoder, the adaptive noise shaping filter to flatten the signal in the frequency spectrum corresponding to the frequency spectrum of the low pass filter Configured In one embodiment, the adaptive noise shaping filter is configured to not flatten frequencies beyond the edge frequency of the low pass filter. In one embodiment, the edge frequency is 25 kHz. In one embodiment, the adaptive noise shaping filter generates a signal indicative of the filter coefficients of the adaptive noise shaping filter, and the signal indicative of the filter coefficients of the adaptive noise shaping filter is included in the bit stream output by the encoder. In one embodiment, the encoder includes an encoding circuit configured to generate a codeword based on the quantized signal word generated by the adaptive quantizer. In one embodiment, the coding circuit is an end of the signal channel of the signal to be coded and of the end of the signal to be coded, wherein the quantization signal word is not associated with the corresponding coding codeword. Configured to generate an escape code according to at least one of In one embodiment, the encoding circuit is configured to generate a codeword using Huffman encoding. In one embodiment, the adaptive quantizer is a variable rate quantizer. In one embodiment, the step size and bit rate of the quantized signal generated by the adaptive quantizer are variable. In one embodiment, the adaptive quantizer is
_{d n + 1 = βd n +} m (c n / L factor)
Are configured to control the step size, where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, m (C _n / L _factor ) is a logarithmic multiplier selected based on the current quantization signal c _n and the load factor L _factor , β is a leakage factor, and d _{n + 1} is the next quantized signal word c _{n + 1} Corresponds to the step size in the log domain applied to. In one embodiment, the adaptive quantizer is
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
Are configured to control the step size, where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, m (C _n / L _factor ) is a logarithmic multiplier selected based on the current quantization signal c _n and the loading factor L _factor , β is a leakage factor, d _min is a threshold step size in the logarithmic domain, d _{n + 1} corresponds to the step size of the log domain applied to the next quantized signal word c _{n + 1} .

In one embodiment, the method comprises the step of filtering the input signal, the filtering comprising using a low pass filter with the determined filter coefficients, the method being filtered using a feedback loop Coding the input signal, wherein the coding step uses an adaptive quantizer to generate a quantized signal based on the difference signal, the inverse quantizer, and the frequency response of the low pass filter Generating a feedback signal based on the quantized signal using the predictor circuit having the determined control parameter; and generating a difference signal based on the feedback signal and the filtered input signal. In one embodiment, the determined filter coefficients of the low pass filter are fixed filter coefficients of the low pass filter, the predictor circuit comprises a finite impulse response (FIR) filter, and the determined control parameters of the predictor circuit are FIR Contains the fixed filter coefficients of the filter. In one embodiment, the filtering step comprises using an adaptive noise shaping filter to filter the signal output by the low pass filter, the adaptive noise shaping filter being in a frequency spectrum corresponding to the frequency spectrum of the low pass filter. Flatten the signal. In one embodiment, the method includes the steps of generating a signal indicative of the filter coefficients of the adaptive noise shaping filter, and including in the encoded bit stream a signal indicative of the filter coefficients of the adaptive noise shaping filter. In one embodiment, the method comprises generating a codeword based on the quantized signal word generated by the adaptive quantizer. In one embodiment, the method comprises at least one of the end of the signal channel of the signal to be encoded and the end of the signal to be encoded, wherein the quantized signal word is not associated with the corresponding encoding codeword Generating an escape code according to one. In one embodiment, the method determines the step size of the adaptive quantizer
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
And c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, and m (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantization signal c _n and the loading factor L _factor , β is a leakage factor, d _min is a threshold step size in the logarithmic domain, and d _{n + 1} is The step size in the logarithmic domain applied to the quantized signal word c _{n + 1} of.

In one embodiment, the content of the non-transitory computer readable medium configures the signal processing circuit to perform the method, the method comprising the step of filtering the input signal, using the determined filter coefficients Low-pass filtering, and encoding the filtered input signal using feedback, wherein the encoding step generates a quantized signal based on the difference signal, and low-pass filtering Generating a prediction signal based on the quantized signal using the control parameter determined based on the frequency response of and generating a difference signal based on the prediction signal and the input signal. In one embodiment, the determined filter coefficients of the low pass filtering are fixed filter coefficients of the low pass filter, and generating the prediction signal comprises using a finite impulse response (FIR) filter, the determined control parameters Contains the fixed filter coefficients of the FIR filter. In one embodiment, the filtering includes adaptive noise shaping that flattens the signal in the frequency spectrum that corresponds to the frequency spectrum of the low pass filter. In one embodiment, the method determines the step size of the quantization signal generation
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
And c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, and m (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantization signal c _n and the loading factor L _factor , β is a leakage factor, d _min is a threshold step size in the logarithmic domain, and d _{n + 1} is The step size in the logarithmic domain applied to the quantized signal word c _{n + 1} of.

  In one embodiment, the system includes an encoder having a determined filter coefficient and including a low pass filter configured to filter the input signal, the encoder generating the quantized signal based on the difference signal. A quantizer, an inverse quantizer, and a predictor circuit, the inverse quantizer being coupled between the adaptive quantizer and the predictor circuit, wherein the predictor circuit is based on the frequency response of the low pass filter With the determined control parameters, the system further includes a decoder configured to decode the signal encoded by the encoder. In one embodiment, the determined filter coefficients of the low pass filter are fixed filter coefficients of the low pass filter, the predictor circuit comprises a finite impulse response (FIR) filter, and the determined control parameters of the predictor circuit are FIR Contains the fixed filter coefficients of the filter. In one embodiment, the system includes an adaptive noise shaping filter coupled between the low pass filter and the adaptive quantizer, wherein the adaptive noise shaping filter flattens the signal in the frequency spectrum corresponding to the frequency spectrum of the low pass filter. Configured to In one embodiment, the adaptive noise shaping filter generates a signal indicative of the filter coefficients of the adaptive noise shaping filter, and the signal indicative of the filter coefficients of the adaptive noise shaping filter is included in the bit stream output by the encoder to the decoder. In one embodiment, the encoder includes an encoding circuit configured to generate a codeword based on the quantized signal word generated by the adaptive quantizer, and the decoder is configured to generate a code generated by the encoding circuit. And a decoding circuit configured to generate the quantized signal word based on the word. In one embodiment, the encoding circuit and the decoding circuit are configured to use escape encoding.

  In one embodiment, the system is configured to have the control parameters determined and to limit the bandwidth of the input signal to less than 75% of the available bandwidth based on the sampling frequency of the input signal. A filter and an encoder configured to generate a quantized signal based on the difference signal, the encoder being configured to generate an adaptive quantizer and a feedback signal, and an inverse quantizer and a prediction And a feedback circuit having a comparator circuit, the predictor circuit having control parameters determined based on the frequency response of the input filter. In one embodiment, the system includes a decoder configured to decode the signal encoded by the encoder. In one embodiment, the input filter is a low pass filter, the determined filter coefficients of the low pass filter are fixed filter coefficients of the low pass filter, and the predictor circuit comprises a finite impulse response (FIR) filter The determined control parameters include fixed filter coefficients of the FIR filter. In one embodiment, the input filter is a band pass filter, the determined filter coefficients of the band pass filter are fixed filter coefficients of the band pass filter, and the predictor circuit comprises a finite impulse response (FIR) filter and the prediction The determined control parameters of the circuit include the fixed filter coefficients of the FIR filter.

  In one embodiment, the system determines based on the frequency response of the low pass filtering means, means for low pass filtering the input signal using the determined filtering parameters, means for generating a quantized signal based on the difference signal, and Means for generating a prediction signal based on the quantized signal using the determined control parameters, and means for generating a difference signal. In one embodiment, the system comprises means for decoding the coded signal. In one embodiment, the means for low pass filtering comprises a low pass filter with fixed filter coefficients and the means for predicting comprises a finite impulse response (FIR) filter with fixed filter coefficients based on the filter coefficients of the low pass filter.

FIG. 2 is a functional block diagram of an embodiment of an ADPCM encoder. FIG. 7 is a functional block diagram of an embodiment of an ADPCM decoder. FIG. 5 is a functional block diagram of one embodiment of a quantizer step size control circuit. FIG. 2 is a functional block diagram of an embodiment of an ADPCM encoder. 3 illustrates an exemplary frequency response of one embodiment of a low pass filter. 7 illustrates an embodiment of a method of controlling a change in adaptive quantizer step size. FIG. 7 is a functional block diagram of an embodiment of an ADPCM decoder. FIG. 5 is a functional block diagram of one embodiment of a quantizer step size and bit rate control circuit. FIG. 7 illustrates an embodiment of a method of generating a codeword and controlling changes in adaptive quantizer step size. FIG. 7 illustrates an embodiment of a method of generating quantized signal values from a codeword.

  In the following description, specific details are set forth to provide a thorough understanding of various embodiments of the devices, systems, methods, and articles. However, one skilled in the art will understand that other embodiments may be practiced without these details. In other instances, well-known structures and methods relating to, for example, finite impulse response filters, encoders, decoders, audio and digital signal processing circuits, etc. such as transistors, multipliers, integrated circuits etc. are unnecessarily obscured of the embodiments. It is not shown or described in detail in some of the figures in order to avoid explanation.

  Throughout the specification and claims, the word "comprise" and its variants "comprehensive" and "including" are to be interpreted in an open and inclusive sense, unless the context indicates otherwise. It should be taken, meaning "including but not limited to".

  Throughout the specification, "one embodiment" or "embodiment" means that the specific feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearances of the phrase “in one embodiment” or “in an embodiment” in various places in the specification are not necessarily all referring to the same or all embodiments. Furthermore, the particular features, structures or characteristics may be combined in any suitable manner in one or more embodiments to obtain further embodiments.

  Headings are provided for convenience only and do not interpret the scope or meaning of the present disclosure.

  The sizes and relative positions of elements in the drawings are not necessarily drawn to scale. For example, the shapes and angles of the various elements are not drawn to scale, and some of these elements are enlarged and arranged to improve the readability of the drawing. Furthermore, the particular shape of the drawn element is not necessarily intended to convey information about the actual shape of the particular element, but is chosen only to facilitate the recognition of the drawing.

  FIG. 1 is a functional block diagram of an embodiment of an audio signal encoder 100 that may employ adaptive differential pulse code modulation (ADPCM). As shown in FIG. 1, the encoder 100 includes a decoder circuit 130 including an adder circuit 110, an adaptive quantization circuit 120, an inverse quantization circuit 134 and a predictor circuit 138, a quantizer step size control circuit 140, and an optional A coder circuit 150 is included.

  In operation of one embodiment, the analog input audio signal to be encoded is received at the positive input 112 of the adder 110 of the encoder 100. The negative input 114 of the adder 110 receives the prediction signal generated by the decoder 130 as a feedback signal. The adder 110 generates a differential signal that is supplied to the adaptive quantization circuit 120. The adaptive quantization circuit 120 may be an analog to digital converter that samples the received differential signal and generates an output signal that represents the differential signal as a series of quantized signals that represent different signal levels. For example, an 8-bit word can be used to represent 256 different signal levels (eg, 256 different steps with uniform step sizes), and a 4-bit word can be used to represent 16 different signal levels it can. Optionally, coding such as Huffman coding and / or arithmetic coding may be used for the quantized signal in one embodiment by the coding circuit 150 generating the coded signal output. The quantized signal output by the adaptive quantization circuit 120 (of the optional coder 150 if a coder is used) is the output quantized signal or codeword of the encoder 100. The quantizer step size control circuit 140 generates a control signal to control the size of the quantizer steps used by the quantizer 120 (and the dequantizer 134), the size varying dynamic range May be modified to facilitate efficient transmission, storage, etc. in view of the audio signal having.

  The inverse quantizer 134 of the decoder 130 generates a signal such as an analog signal based on the quantization signal output by the adaptive 25 quantizer and the current step size control signal setting by the quantizer step size control circuit 140. Do. The predictor circuit 138 may generate a prediction signal based on the output signal of the inverse quantizer 134 and historical data such as recent quantization signal values and recent prediction signal values. One or more filters and one or more feedback loops may be used by the predictor circuit 138.

  As shown, the encoder 100 of FIG. 1 includes one or more processors or processor cores P, one or more memories M, and discrete circuits DC, which are solely used to implement the functions of the encoder 100. Or in various combinations. In operation, one embodiment of encoder 100 generates quantized, optionally encoded data from an input analog audio signal. In operation of one embodiment, a digital audio signal to be encoded (eg, to a reduced bit stream) may be received at positive input 112 instead of an analog signal (eg, an 8-bit digital audio signal is Encoded into a 4-bit digital audio signal).

  Although the components of encoder 100 of FIG. 1 are shown as separate components, the various components may be combined (eg, in some embodiments, quantizer step size control circuit 140 May be integrated into the adaptive quantizer 120) and may be divided into additional components (eg, the predictor circuit 138 may be divided into multiple predictor circuits, filters, adders, buffers) , And may be divided into separate components such as look-up tables, and various combinations thereof.

  FIG. 2 is a functional block diagram of an embodiment of an audio signal decoder 200 that can use adaptive differential pulse code modulation (ADPCM). The decoder 200 can be used, for example, as the decoder 130 of FIG. 1 as a separate decoder for decoding received encoded signals and the like. As shown in FIG. 2, the decoder 200 includes an optional decoding circuit 250, an inverse quantization circuit 234, a predictor circuit 238, an inverse quantizer step size control circuit 240, and an adder 270.

  In operation of one embodiment, the coded signal is received by a decoding circuit 250 that converts the coded signal to a quantized signal. The quantized signal to be decoded is supplied to the inverse quantizer 234 and the inverse quantizer step size control circuit 240. If the decoder 200 is used for an encoder such as the encoder 100 of FIG. 1, the decoding circuit 250 may typically be omitted, and the same step size control circuit may be used to quantizer and dequantize the step size control signal. Supply (see Figure 1). The dequantizer 234 is configured by the dequantizer step size control circuit 240 with the quantized signal output by the decoding circuit 250 (or received from the quantizer (see the quantizer 120 of FIG. 1)). Based on the set current step size, a signal such as an analog signal is generated. The output of dequantizer 234 is provided to a first positive input of summer 270. The output of the adder is provided to a predictor 238 which includes a finite impulse response (FIR) filter as shown. The output of the FIR filter is provided to a second positive input of summer 270.

  If decoder 200 is used as a decoder to provide the decoded signal as an output, the output of decoder 200 is the output of adder 270. When the decoder 200 is used in the encoder as part of a feedback loop, such as the decoder 130 used in the encoder 100 of FIG. 1, the output of the predictor circuit 238 provides a prediction signal to the encoder (Summing of FIG. See the prediction signal provided to the negative input 114 of the unit 110).

  Inverse quantizer 234, inverse quantizer step size control circuit 240 and predictor circuit 238 can generally operate in a manner similar to corresponding components of an encoder such as encoder 100 of FIG. For example, referring to FIGS. 1 and 2, when the corresponding components are operated in a similar manner at encoder 100 and decoder 200, there is no need to exchange additional control signals between encoder 100 and decoder 200. The quantization signal is used to generate a prediction signal to facilitate controlling the step size of both the encoder 100 and the decoder 200.

  As shown, the decoder 200 of FIG. 2 includes one or more processors or processor cores P, one or more memories M, and individual circuits DC, which are solely used to implement the functions of the decoder 200. Or in various combinations. Although the components of decoder 200 of FIG. 2 are shown as separate components, the various components may be combined (eg, in some embodiments, inverse quantizer step size control circuit 240) (Which may be integrated into the inverse quantizer 234) and may be divided into additional components (eg, the predictor circuit 238 into separate components such as filters, adders, buffers, look-up tables, etc.) There may be divisions), and various combinations thereof.

  3 may be used, for example, as quantizer step size control circuit 140 in the embodiment of encoder 100 of FIG. 1 or as dequantizer step size control circuit 240 in the embodiment of decoder 200 of FIG. 10 is a functional block diagram of an embodiment of quantizer step size control circuit 340. FIG. As shown, quantizer step size control circuit 340 includes a logarithmic multiplier selector 342 that selects a logarithmic multiplier based on the current quantized signal word, such as the word output by adaptive quantizer 320. . In some embodiments, the current quantized signal word may be included in the bitstream decoded by the decoder (see FIG. 2). Logarithmic multiplier selector 342 can select a logarithmic multiplier based on historical data, such as previously quantized signal words, for example, a lookup table that can be updated during an update download, etc. based on historical data. It may include a LUT. Log multiplier selector 342 can select a log multiplier based on statistical probabilities based on current and previous quantized signal words. The quantizer step size control circuit 340 includes an adder 344 that receives the selected logarithmic multiplier at a first positive input and provides an output to a delay circuit 346. The output of delay circuit 346 is provided to multiplier 348 and exponent circuit 350. Multiplier 348 multiplies the output of delay circuit 346 by a scaling factor or leakage factor β that is typically close to 1 and less than 1 and supplies the result to the second positive input of adder 344. The leakage factor may be typically constant, but in some embodiments may be variable based on, for example, previous step size control signals or other historical data. Choosing the scaling factor β close to 1 and less than 1 facilitates reducing the impact of choosing an incorrect step size, eg, for transmission errors, as the introduced error will collapse.

  The exponent circuit 350 generates a step size control signal based on the output of the delay circuit 346 during operation. As shown, the step size control signal is provided to adaptive quantizer 320 and inverse quantizer 334. As shown, quantizer step size control circuit 340 operates logarithmically and can simplify calculations. Some embodiments can operate linearly, for example, using a multiplier instead of adder 244 and an exponent circuit instead of multiplier 246. The illustrated quantizer step size control circuit 340 operates logarithmically, and the step size selected based on the step size control signal varies exponentially.

In one embodiment, quantizer step size control circuit 340 may operate according to Equation 1 below:
d _{n + 1} = β d _n + m (c _n ). . . Formula 1
Here, d _n is a step size in the logarithmic domain, m (c _n ) is a logarithmic multiplier selected based on the current quantization signal, and β is a scaling factor or a leakage factor. As shown, FIG. 3 includes one or more processors P, one or more memories M, and an individual circuit DC, which are solely used to implement the functions of quantizer step size control circuit 340. Or in various combinations.

  Although the components of FIG. 3 are shown as separate components, the various components may be combined (e.g., integrating adder 344 and multiplier 348 into an arithmetic processor in some embodiments) Can be divided into additional components, and there are various combinations of them.

  FIG. 4 is a functional block diagram of an audio signal encoder 400 that can use adaptive differential pulse code modulation (ADPCM). The audio signal encoder 400 of an embodiment provides additional bandwidth control to help avoid quantizer overload and includes adaptive noise shaping. As shown in FIG. 4, the encoder 400 includes a low pass filter 475, an adaptive noise shaping filter 480, an adder circuit 410, a variable rate adaptive quantizer circuit 420, a decoder circuit 430 including an inverse quantizer circuit 434, and a predictor Circuit 438, quantizer step size and average bit rate control circuit 440, coder 450 and bitstream assembler 485.

  In operation of one embodiment, the analog input audio signal to be encoded is received at the input of an input filter, such as the low pass filter 475 shown. Low pass filter 475 facilitates signal to noise ratio improvement. The low pass filter 475 may be, for example, an FIR filter with 25 kHz edges and a 30 kHz stop band, which has been found to provide excellent results for data sampled at 88.2 kHz or 96 kHz. FIG. 5 shows an exemplary frequency response of an embodiment of low pass filter 475 applied to a 96 kHz sampling rate. A sufficiently high sampling rate is used by using a low pass filter with control parameters based on the control parameters of the input filter and a corresponding fixed prediction filter (for example a predictor with filter coefficients based on the frequency response of the input filter) In this case, it is easy to obtain a substantial prediction gain for the input signal, which makes it easy to obtain the desired minimum signal to noise ratio. In testing, sampling rates below 48 kHz (e.g. 44.1 kHz and 48 kHz) generally do not provide sufficient improvement in gain.

  The output of low pass filter 475 is provided to adaptive noise shaping filter 480. In some embodiments, low pass filter 475 may be omitted, and the signal to be encoded may be input to adaptive noise shaping filter 480 instead of low pass filter 475. In some embodiments, the adaptive noise shaping filter 480 may be omitted or selectively bypassed. For example, if high bit rate signal coding is used, adaptive noise shaping filter 480 may be omitted or bypassed. In some embodiments, a band pass filter may be used instead of a low pass filter to make corresponding adjustments to the prediction filter. For example, an embodiment of an input filter (eg, a band pass filter) configured to have a fixed control parameter and limit the bandwidth of the input signal to less than 75% of the available bandwidth based on the sampling frequency. A corresponding decoder can be used and can include predictor circuits with fixed control parameters based on the frequency response of the filter. Using the input filter to limit the bandwidth of the input signal and setting the control parameters of the predictor circuit based on the frequency response of the input filter is an input signal if a sufficiently high sampling rate is used It makes it easy to obtain a substantial prediction gain for, which makes it easy to obtain the desired minimum signal to noise ratio.

  The adaptive noise shaping filter 480 may be, for example, a low order all zero linear prediction filter. Real coefficients (not complex coefficients) can be used. In one embodiment, the adaptive noise shaping filter 480 maintains the full spectral slope and masking sufficient to maintain the transmission codec (eg, compression artifacts generally imperceptible) while the signal received from the low pass filter 475 is It is an all zeros adaptive noise shaping filter that flattens the spectrum. A corresponding decoder (see decoder 700 in FIG. 7) can use all-pole filters that use the same coefficients to recover the original spectral shape. In one embodiment, adaptive noise shaping filter 480 preserves the whiteness reference of predictor circuit 438. For example, the low order noise shaping filter 480 may be adjusted to not flatten the signal beyond the low pass filter edge frequency (eg, 25 kHz, which may not be present in the signal filtered by the low pass filter 475) it can. As mentioned above, the loss of energy at high frequencies facilitates higher prediction gains. Filters other than linear prediction filters can be used as noise shaping filters.

  Adaptive noise shaping filter 480 provides the filtered output signal to positive input 412 of summer 410. In one embodiment, adaptive noise shaping filter 480 also provides a signal that includes adaptive noise filter setting information and / or synchronization information, which includes adaptive noise filter setting and synchronization information corresponding reverse noise shaping filter 780. Can be used to communicate to a decoder, such as decoder 700 of FIG. Configuration and synchronization information may be sent periodically, such as once every 512 sample blocks. In some embodiments, adaptive noise shaping filter control information may be implicitly included in the bitstream of the bitstream. For example, if the codeword of the bitstream indicates an average bit rate higher than the threshold average bit rate, this may indicate that adaptive noise shaping has been bypassed.

  The negative input 414 of the adder 410 receives the prediction signal generated by the decoder 430 as a feedback signal. A summer 410 generates a differential signal that is provided to variable rate adaptive quantizer circuit 420.

  A variable rate adaptive quantizer circuit 420 produces an output signal that represents the differential signal as a series of quantized signals or words. The size of the quantized signal is not fixed and the average length can be adjusted using the step size and output of the multiplier table of the average bit rate controller 440, as described in more detail below. The output of variable rate adaptive quantizer circuit 420 is provided to step size and average bit rate controller 440, inverse quantizer 434, and coder 450.

  The quantizer step and average bit rate control circuit 440 generates one or more control signals to control the size of the quantizer step. This implicitly determines the average length of the quantized signal used by the quantizer 420 (and the inverse quantizer 434), which takes into account the input audio signal with a fluctuating dynamic range It can be modified by adjusting the multiplier table to facilitate efficient coding.

ここでｃ_ｎは現在の量子化信号であり、ｅ_ｎは誤差または差分信号であり、ｄ_ｎは対数領域における現在のステップサイズに対応する。 FIG. 6 shows an embodiment of a method 600 for generating codewords and controlling changes in step size and average bit rate that may be used, for example, by the encoder 400 of FIG. For convenience, the method 600 is described with reference to the encoder 400 of FIG. The method starts at 602 and proceeds to 604. At 604, variable rate adaptive quantizer 420 generates a current quantized signal or word based on the difference signal and the current quantizer step size control signal. This can be done, for example, according to equation 2 below:

Where c _n is the current quantized signal, e _n is the error or difference signal, and d _n corresponds to the current step size in the logarithmic domain.

The method proceeds from 604 to 606. At 606, the quantizer step size and average bit rate control circuit 440 generates one or more control signals to set the step size of the next quantized signal word. This can be done, for example, according to equation 1 above, or according to equation 3 or 4 below:
_{d n + 1 = βd n +} m (c n / L factor). . . Formula 3
Where c _n is the current quantization signal, d _n corresponds to the current step size and accordingly the bit length, and L _factor is the load used to control the average bit length (and hence the average bit rate) It is a coefficient, m (c / L _factor ) is a logarithmic multiplier selected based on the current quantization signal and the loading factor, and β is a leakage factor. In some embodiments, the minimum step size d _min in the logarithmic domain can be set as follows.
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min ). . . Formula 4

The loading factor L _factor can be chosen to maintain the desired average bit rate. The loading factor may typically be between 0.5 and 16. In some embodiments, a maximum step size can be used. By changing the logarithmic multiplier m (c _n / L _factor ), the bit rate and step size are changed, and the values stored in the look-up table of the logarithmic multiplier selector (see FIG. 8) are changed by the adaptive quantizer 420. And is selected to cause the dequantizer 434 to perform the desired change in step size bit rate. For example, higher log multipliers may indicate an increase in step size and bit rate to quantizer 420 and inverse quantizer 434. The look-up table may be indexed based on the result of dividing the current quantization value c _n by the loading factor L _factor . Different look-up tables can be used instead of, or in addition to, different loading factors to replace L _factor . In one embodiment, the values in the look-up table can be selected such that the log multiplier is monotonically increasing as the current quantization value c _n increases, and the table of multipliers can be selected from small negative values of c _n Go to large positive values of c _n .

  The method 600 proceeds from 606 to 608. At 608, the encoder 400 determines whether to continue encoding the received signal. If it is determined at 608 to continue encoding the received signal, the method returns to 604 to process the next quantized signal word. If it is not determined at 608 to continue encoding the received signal, the method proceeds to 610 where other processing is performed, such as generating an escape code indicating that the received signal has ended. The method proceeds from 610 to 612 and the method 600 ends.

  Some embodiments of encoder 400 may perform other operations not shown in FIG. 6 and may not perform all of the operations shown in FIG. 6 and perform the operations of FIG. 6 in a different order You may

Referring to FIG. 4, the inverse quantizer 434 of the decoder 430 generates a signal such as an analog signal based on the quantized signal output c _n by the variable rate adaptive quantizer 420 and the current step size d _n. . The predictor circuit 438 is based on the output signal of the inverse quantizer 434 and historical data such as recent encoded data and recent predicted values, as described in more detail below with reference to FIG. A prediction signal can be generated. Predictor circuit 438 may use an FIR filter with coefficients selected based on the frequency response of low pass filter 475, as described in more detail below with reference to FIG. These coefficients may be fixed and may be selected to facilitate maintenance of a sufficient signal to noise ratio for the expected input signal characteristics. Tests have shown that using the fixed coefficients of the FIR filter in the predictor circuit 438 based on the frequency response of the low pass filter 475 significantly improves the signal to noise ratio of signals above 64 kHz. For example, attenuating energy above 25 kHz with low pass filter 475 and selecting a fixed factor of the FIR filter based on the frequency response of the low pass filter yields a predicted gain of 45 dB in the embodiment. Using an 8-bit quantizer (see adaptive quantizer 120 of FIG. 1, which may be an 8-bit quantizer, 4-bit quantizer, etc.), coding without an adaptive noise shaping filter (FIG. 1) A signal to noise ratio comparable to (see) is obtained, but frequencies above 25 kHz are not included.

  In one embodiment, the quantized signal output by variable rate adaptive quantizer circuit 420 (of optional coder 450 if a coder is used) is the output quantized signal of encoder 400. Optionally, coding such as Huffman coding and / or arithmetic coding may be used for the quantized signal in one embodiment by the coding circuit 450 that generates the coded signal output of the coding circuit 400 . The coder 450 converts the quantized signal words into codewords using, for example, one or more look-up tables. Infrequently used quantized signal words can be assigned to larger codewords, and frequently used quantized signal words can be assigned to smaller codewords to increase the efficiency of coder 400 .

  The coder 450 optionally provides escape coding in one embodiment. For example, for quantized values not included in the codebook used (eg, the Huffman codebook), an escape code may be sent instead of a codeword from the codebook, the escape code being a quantized signal value Or the form of transmission of the information (eg, that the actual quantization signal is being transmitted, that the next codeword is a quantization signal value instead of a codeword, the difference between maximum / minimum levels is being transmitted And so on). In another example, the escape code can indicate that the channel of the coded signal is interrupted or absent (e.g., only one channel of the stereo signal is coded). In another example, the escape code can indicate the end of the encoded signal.

  The bitstream assembler 485 receives the codewords output by the coder 450 and the adaptive noise shaping filter control / synchronization information output by the adaptive noise shaping filter 480 and transmits the bitstream to a decoder and / or storage device. Assemble. In some embodiments, data packets, such as packets containing 512 sample blocks and sample block adaptive noise shaping filter control / synchronization information, can be assembled by bitstream assembler 485.

  FIG. 7 is a functional block diagram of an embodiment of an audio signal decoder 700 that may employ adaptive differential pulse code modulation (ADPCM). The decoder 700 can be used, for example, as the decoder 430 of FIG. 4 as a separate decoder for decoding received coded signals and the like. As shown in FIG. 7, the decoder 700 includes a bitstream disassembler 785, an option code word decoding circuit 750, an inverse quantizer circuit 734, a predictor circuit 738, an inverse quantizer step size and average bit rate control circuit 740, An adder 770, an inverse adaptive noise shaping filter 780, and a low pass filter 775 are included.

In operation of one embodiment, the assembled signal is received by the bitstream disassembler 785 and split into an encoded signal component and an adaptive noise shaping filter control and synchronization signal component. The encoded signal component is supplied to the decoding circuit 750, which converts the encoded signal into a quantized signal c _n . Escape coding may be used in one embodiment, as described above with reference to coder 450 of FIG. The quantized signal to be decoded is provided to an inverse quantizer 734 and an inverse quantizer step size and average bit rate control circuit 740. If the decoder 700 is used in an encoder such as the encoder 400 of FIG. 4, the decoding circuit 750 may typically be omitted, and the same step size and average bit rate control circuit may be used to inverse quantize the step size control signal. May be supplied to the chemical reactor (see FIG. 4).

  Inverse quantizer 734 is a quantization signal output by decoding circuit 750 (or received from quantizer (see quantizer 420 in FIG. 4)) and inverse quantizer step size and average bit rate control Based on the current step size set by circuit 740, a signal such as an analog signal is generated. The output of inverse quantizer 734 is provided to a first positive input of summer 770. The output of summer 770 is provided to predictor 738, which includes a finite impulse response (FIR) filter as shown. The output of the FIR filter is provided to a second positive input of summer 770.

  When the decoder 700 is used as a decoder and as a decoder providing the decoded signal as an output, the output of the decoder 700 is provided to an inverse filter, such as the illustrated inverse adaptive noise shaping filter 780. The inverse adaptive noise shaping filter 780 may be, for example, a low order all-pole linear prediction filter. In one embodiment, inverse adaptive noise shaping filter 780 uses the same coefficients used by the corresponding adaptive noise shaping filter (eg, adaptive noise shaping filter 480 of FIG. 4) of the corresponding encoder as the coefficients of the all-pole filter Is an all-pole adaptive noise shaping filter that uses to restore the spectrum of the signal. This information is conveyed in a bit stream and is supplied by the disassembler 785 to the inverse adaptive noise shaping filter 780. Configuration and synchronization information may be provided periodically, such as once every 512 sample blocks. In some embodiments, inverse adaptive noise shaping filter control information may be implicitly included in the bitstream of the bitstream, eg, as described above with reference to FIG.

  The output of inverse adaptive noise shaping filter 780 is optionally filtered by low pass filter 775. This facilitates the removal of recovered high frequency energy when the original spectrum of the signal is recovered by the inverse adaptive noise shaping filter 780. In one embodiment, the low pass filter 775 of the decoder 700 can use the same coefficients as used by the corresponding low pass filter (eg, low pass filter 475 of FIG. 4) of the encoder.

  When the decoder 700 is used in the encoder as part of a feedback loop, such as the decoder 430 used in the encoder 400 of FIG. 4, the output of the predictor circuit 738 provides a prediction signal to the encoder (Summing in FIG. 4) See the prediction signal provided to the negative input 414 of the signal generator 410).

  Inverse quantizer 734, inverse quantizer step and average bit rate control circuit 740, and predictor circuit 738 can generally operate in a manner similar to the corresponding components of an encoder such as encoder 400 of FIG. . For example, referring to FIGS. 4 and 7, operating the corresponding components in encoder 400 and decoder 700 in a similar manner may result in quantum without the need to exchange additional control signals between encoder 400 and decoder 700. The generation signal is used to generate a prediction signal, which facilitates controlling the step size and average bit rate of both the encoder 400 and the decoder 700. For example, a system including an embodiment of encoder 400 and an embodiment of decoder 700 may operate using the same control parameters (eg, using the same filter coefficients) for corresponding components.

  As shown, the decoder 700 of FIG. 7 includes one or more processors or processor cores P, one or more memories M, and individual circuits DC, which are solely used to implement the functions of the decoder 700. Or in various combinations. Although the components of the decoder 700 of FIG. 7 are shown as separate components, the various components may be combined (e.g., in some embodiments, inverse quantizer steps and average rate control) Circuit 740 may be integrated into inverse quantizer 734) and may be divided into additional components (eg, predictor circuit 738 may be a separate configuration such as a filter, adder, buffer, look-up table, etc. There may be divided into elements), and various combinations thereof.

FIG. 8, for example, as quantizer step size and average bit rate control circuit 440 in the embodiment of encoder 400 of FIG. 4 or inverse quantizer step size and average bit rate control in the embodiment of decoder 700 of FIG. FIG. 16 is a functional block diagram of an embodiment of quantizer step size and average rate control circuit 840 that may be used as circuit 740. As shown, the quantizer step size and average bit rate control circuit 840 includes a multiplier 852 that receives the current quantized signal word c _n and the inverse of the load factor L _factor , the current quantized signal word and the load factor And a logarithmic multiplier selector 842 for selecting a logarithmic multiplier based on. As shown, the current quantized signal word is the word output by variable rate adaptive quantizer 820. In some embodiments, the current quantized signal word may be included in the bitstream decoded by the decoder (see FIG. 7). Logarithmic multiplier selector 842 can select a logarithmic multiplier based on historical data, such as previously quantized signal words, for example, a look-up table that can be updated during an update download, etc. based on historical data. It may include a LUT. Log multiplier selector 842 may select a log multiplier based on statistical probabilities based on current and previous quantized signal words. The quantizer step size and average bit rate control circuit 840 includes an adder 844 that receives the selected logarithmic multiplier at a first positive input and provides an output to a delay circuit 846. The output of delay circuit 846 is provided to multiplier 848 and exponent circuit 850. Multiplier 848 multiplies the output of delay circuit 846 by a scaling factor or leakage factor β, which is typically close to 1 and less than 1, and supplies the result to the second positive input of adder 844. The leakage factor may be typically constant, but in some embodiments may be variable based on, for example, previous step size control signals or other historical data. Choosing the scaling factor β close to 1 and less than 1 facilitates reducing the impact of choosing an incorrect step size, eg, for transmission errors, as the introduced error will collapse.

  The exponent circuit 850 generates a step size control signal based on the output of the delay circuit 846 during operation. As shown, the step size and average bit rate control signals are provided to variable rate adaptive quantizer 820 and dequantizer 834. As shown, quantizer step size and average bit rate control circuit 840 operates logarithmically and can simplify calculations. Some embodiments may operate in a linear fashion, for example, using a multiplier instead of adder 844 and an exponent circuit or the like instead of multiplier 846. The illustrated step size and average bit rate control circuit operates logarithmically, and the step size selected based on the step size control signal varies exponentially. In one embodiment, quantizer step size and average bit rate control circuit 840 operates in accordance with Equation 3 or Equation 4 and generates a look-up table as described in more detail above with reference to FIGS. 4 and 6. Log multiplier values may be selected to do this.

  As shown, FIG. 8 includes one or more processors P, one or more memories M, and an individual circuit DC, which implement the functions of the quantizer step size and average bit rate control circuit 840. , Alone or in various combinations. The illustrated components, such as adders, multipliers, etc., may be implemented in various ways such as using discrete circuits, executing instructions stored in memory, using look-up tables, etc., and various combinations thereof. May be

  FIG. 9 generates a codeword from an audio signal when escape coding is used, for example, of a method 900 of controlling changes in quantizer step size and average bit rate that may be used by the encoder 400 of FIG. An embodiment is shown. For convenience, the method 900 is described with reference to the encoder 400 of FIG. The method starts at 902 and proceeds to 904. At 904, the encoder 400 collects blocks of audio samples and proceeds to 906. At 906, encoder 400 processes the samples for each channel. Parallel processing of samples of the channel can be used.

  At 906a, adaptive quantizer 420 determines whether the channel has audio samples to be processed. If the channel has audio samples, method 900 proceeds from 906a to 908. At 908, coder 450 determines whether the quantized samples have corresponding symbols in a codebook, which is a Huffman codebook as shown. If it is determined that the quantized samples have corresponding symbols in the codebook, the method proceeds from 908 to 910. At 910, the coder 450 writes the corresponding symbols to the bitstream. The method 900 proceeds from 910 to 914.

  At 908, if it is not determined that the quantized sample has the corresponding symbol in the codebook, method 900 proceeds from 908 to 912. At 912, the coder writes embedded escape codes and quantized sample values to the bitstream, such as the embedded escape code followed by the illustrated 16-bit quantized sample values. As described in more detail above, other methods can be used to transmit the quantized sample values without corresponding codewords in the codebook. The method proceeds from 912 to 914.

  At 914, the step size and average bit rate control circuit 440 updates the corresponding channel step size control signal, as described in more detail above. For example, Equations 1, 3 and 4 can be used. The method 900 proceeds from 914 to 906 to process the next sample of the channel.

  At 906b, the adaptive quantizer determines if there is audio data in the channel but there are no samples to be processed in the block. For example, the channel may have terminated early. If it is determined that there are no samples in the block in the channel, method 900 proceeds from 906 b to 916. At 916, coder 450 writes an end of channel escape code to the bitstream and processing of the channels in the current block is complete. Method 900 proceeds from 916 to 906.

  At 906c, the encoder 400 determines whether all audio data in blocks of all channels has been processed. If at 906 c it is determined that all audio data in the block has been processed, method 900 proceeds from 906 c to 918. At 918, encoder 400 determines if there is more data to start a new block. If it is determined at step 918 that there is more data to start a new block, method 900 proceeds from 918 to 904 and the next block of audio samples is processed. If at 918 it is not determined that there is data to start a new block, the method proceeds to 920. At 920, the coder 450 writes an end of stream escape code to the bitstream. The method proceeds from 920 to 930 and the processing of the audio signal ends.

  Some embodiments of encoder 400 may perform other operations not shown in FIG. 9 and may not perform all of the operations shown in FIG. 9, and perform the operations of FIG. 9 in a different order You may

  FIG. 10 shows an embodiment of a method 1000 of generating quantized signal values from a codeword used, for example, by the decoder 700 of FIG. 7 when escape coding is used. Method 1000 can process codewords for multiple channels of the signal in parallel. For convenience, the method 1000 is described with reference to the decoder 700 of FIG. The method starts at 1002 and proceeds to 1004. At 1004, decoding circuit 750 receives a codeword (or codewords if channels are being processed in parallel) and proceeds to 1006.

At 1006, decoding circuit 750 determines whether the codeword (symbol) has corresponding quantized sample values in a codebook, such as a Huffman codebook. If it is determined that the codeword (symbol) has a corresponding quantized sample value in the codebook, method 1000 proceeds from 1006 to 1008 and the corresponding quantized sample value is decoded as the current quantized signal value c _n It is output by the circuit 750. The method 1000 proceeds from 1008 to 1004 to process the next codeword of the channel (and the codewords of the other channels of the coded signal). At 1006, if it is not determined that the codeword (symbol) has corresponding quantized sample values in the codebook, method 1000 proceeds from 1006 to 1010.

At 1010, the decoding circuit 750 determines if the codeword is an embedded escape code. If it is determined at 1010 that the codeword is an embedded escape code, method 1000 proceeds from 1010 to 1012 where the next codeword of the channel is output by the decoding circuit 750 as the current quantized signal value c _n . The method 1000 proceeds from 1012 to 1004 to process the next codeword of the channel (and the codewords of the other channels of the encoded signal). At 1010, if the codeword is not determined to be an embedded escape code, method 1000 proceeds from 1010 to 1014.

  At 1014, the decoding circuit 750 determines if the codeword is the end of the channel escape code. If, at 1014, it is determined that the codeword is at the end of the channel escape code, method 1000 proceeds from 1014 to 1016 and processing of the signaling channel ends. The method 1000 proceeds from 1016 to 1004 to process the next codeword of the remaining channel of the signal. At 1014, if the codeword is not determined to be the end of the channel escape code, method 1000 proceeds from 1014 to 1018.

  At 1018, the decoding circuit 750 determines whether the codeword is the end of the signal escape code. If it is determined at 1018 that the codeword is at the end of the signal escape code, method 1000 proceeds from 1018 to 1020 and processing of the signal ends. The method 1000 proceeds from 1020 to 1022 and the method 1000 ends. If, at 1018, the codeword is not determined to be the end of the signal escape code, method 1000 proceeds from 1018 to 1004 and the next codeword (or block) of the channel (and the codeword of the other channel of the encoded signal) Process

  Some embodiments of the decoder 700 may perform other operations not shown in FIG. 10, may not perform all of the operations shown in FIG. 10, and may perform the operations of FIG. 10 in a different order You may

  Some embodiments may take the form of or include a computer program product. For example, according to one embodiment, a computer readable medium is provided that includes a computer program configured to perform one or more of the methods or functions described above. The medium may be, for example, a physical storage medium such as a read only memory (ROM) chip, or a digital versatile disc (DVD-ROM), a disc such as a compact disc (CD-ROM), a suitable drive or a suitable connection. One or more barcodes, which may be hard disks, memory, networks, or portable media media read through, stored on one or more such computer readable media and readable by an appropriate reader Or include those encoded in other related codes.

  Further, in some embodiments, some or all of the methods and / or functions may be implemented or provided at least in part in other ways, such as, but not limited to, firmware and / or hardware Application Specific Integrated Circuits (ASICs), Digital Signal Processors, Discrete Circuits, Logic Gates, Standard Integrated Circuits, Controllers (eg, those that execute appropriate instructions, including microcontrollers and / or embedded controllers), Field Programmable Gate Arrays (FPGA), one or more such as complex programmable logic devices (CPLDs), and devices using RFID technology, and various combinations thereof.

  The various embodiments described above can be combined to provide further embodiments. Aspects of the embodiments can be modified as necessary to use the concepts of the various patents, applications and publications to provide further embodiments.

  These and other changes can be made to the embodiments in light of the above detailed description. In general, in the following claims, the terms used should not be construed as limiting the claims to the specific embodiments disclosed in the specification and the claims, as such The scope of the claims should be construed to include all possible embodiments as well as the full scope of equivalents to which they are entitled. Accordingly, the claims are not limited by the disclosure.

Claims (166)

A low pass filter having the determined filter coefficients and configured to filter the input signal;
An encoder configured to generate a quantization signal based on the difference signal;
The encoder is an adaptive quantizer,
A decoder configured to generate a feedback signal and having an inverse quantizer and a predictor circuit,
The apparatus wherein the predictor circuit has control parameters determined based on the frequency response of the low pass filter.   The determined filter coefficients of the low pass filter are fixed filter coefficients of the low pass filter, the predictor circuit comprises a finite impulse response (FIR) filter, and the determined control parameters of the predictor circuit are: The apparatus of claim 1, comprising fixed filter coefficients of the FIR filter. An adaptive noise shaping filter coupled between the low pass filter and the encoder, wherein the adaptive noise shaping filter is configured to flatten a signal in a frequency spectrum corresponding to a frequency spectrum of the low pass filter. ,
The device of claim 1.   The apparatus of claim 3, wherein the adaptive noise shaping filter is configured not to flatten frequencies above the edge frequency of the low pass filter.   5. The apparatus of claim 4, wherein the edge frequency is 25 kHz.   The adaptive noise shaping filter generates a signal indicating a filter coefficient of the adaptive noise shaping filter, and the signal indicating a filter coefficient of the adaptive noise shaping filter is included in a bit stream output by the encoder. The device according to 3.   The apparatus of claim 1, wherein the encoder comprises encoding circuitry configured to generate a codeword based on the quantized signal word generated by the adaptive quantizer. The coding circuit
The quantized signal word is not associated with the corresponding encoded codeword,
8. The apparatus of claim 7, configured to generate an escape code in response to at least one of an end of a signal channel of a signal to be encoded and an end of the signal to be encoded. .   8. The apparatus of claim 7, wherein the encoding circuit is configured to generate the codeword using Huffman coding.   The apparatus of claim 1, wherein the adaptive quantizer is a variable rate quantizer.   11. The apparatus of claim 10, wherein the step size and bit rate of the quantization signal generated by the adaptive quantizer are variable. The adaptive quantizer is
_{d n + 1 = βd n +} m (c n / L factor)
Are configured to control the step size, where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, m (C _n / L _factor ) is a logarithmic multiplier selected based on the current quantization signal c _n and the load factor L _factor , β is a leakage factor, and d _n +1 is the next quantized signal 11. The apparatus of claim 10, corresponding to the step size of the log domain applied to words c _{n + 1} . The adaptive quantizer is
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
Are configured to control the step size, where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, m (C _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, and d _min is a threshold step size in the logarithmic domain The apparatus according to claim 10, wherein d _n +1 corresponds to the step size of the log domain applied to the next quantized signal word c _{n +1} . Filtering the input signal, wherein the filtering step uses a low pass filter with the determined filter coefficients;
Encoding the filtered input signal using a feedback loop,
The encoding step
Generating a quantized signal based on the difference signal using an adaptive quantizer;
Generating a feedback signal based on the quantized signal using an inverse quantizer and a predictor circuit having control parameters determined based on the frequency response of the low pass filter;
Generating the difference signal based on the feedback signal and the filtered input signal.   The determined filter coefficients of the low pass filter are fixed filter coefficients of the low pass filter, the predictor circuit comprises a finite impulse response (FIR) filter, and the determined control parameters of the predictor circuit are: 15. The method of claim 14, comprising fixed filter coefficients of the FIR filter.   The filtering step includes using an adaptive noise shaping filter to filter the signal output by the low pass filter, the adaptive noise shaping filter being a signal in a frequency spectrum corresponding to a frequency spectrum of the low pass filter. The method according to claim 15, wherein the surface is planarized. Generating a signal indicative of the filter coefficients of the adaptive noise shaping filter; and including the signal indicative of the filter coefficients of the adaptive noise shaping filter in a coded bit stream.
The method of claim 16. Generating a codeword based on the quantized signal word generated by the adaptive quantizer.
The method of claim 14. The quantized signal word is not associated with the corresponding encoded codeword,
The end of the signal channel of the signal to be coded, and the end of the signal to be coded,
Generating an escape code in response to at least one of
The method according to claim 18. The step size of the adaptive quantizer is
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
And c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, and m (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, d _min is a threshold step size of the logarithmic domain, d _{n + 1} Corresponds to the step size of the log domain applied to the next quantized signal word c _{n + 1} ,
The method of claim 14. A non-transitory computer readable medium having content for configuring signal processing circuitry to perform the method, the method comprising:
Filtering the input signal, the filtering including low pass filtering using the determined filter coefficients, and encoding the filtered input signal using feedback, The encoding step
Generating a quantization signal based on the difference signal;
Generating a prediction signal based on the quantized signal using a control parameter determined based on a frequency response of the low pass filtering;
Generating the difference signal based on the predicted signal and the input signal.   The determined filter coefficients of the low pass filtering are fixed filter coefficients of the low pass filter, and the generating of the predictor signal comprises using a finite impulse response (FIR) filter, and the determined control parameters are: 22. The non-transitory computer readable medium of claim 21, comprising fixed filter coefficients of the FIR filter.   23. The non-transitory computer readable medium of claim 22, wherein the filtering step comprises adaptive noise shaping to flatten a signal in a frequency spectrum corresponding to a frequency spectrum of the low pass filter. The method comprises: determining a step size of the generation of the quantized signal;
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
And c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, and m (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, d _min is a threshold step size of the logarithmic domain, d _{n + 1} Corresponds to the step size of the log domain applied to the next quantized signal word c _{n + 1} ,
The non-transitory computer readable medium of claim 14. A low pass filter having the determined filter coefficients and configured to filter the input signal;
An adaptive quantizer configured to generate a quantization signal based on the difference signal;
An inverse quantizer,
An encoder including a predictor circuit,
An encoder, wherein the inverse quantizer is coupled between the adaptive quantizer and the predictor circuit, the predictor circuit having control parameters determined based on the frequency response of the low pass filter;
A decoder configured to decode the signal encoded by the encoder.   The determined filter coefficients of the low pass filter are fixed filter coefficients of the low pass filter, the predictor circuit comprises a finite impulse response (FIR) filter, and the determined control parameters of the predictor circuit are: 26. The system of claim 25, comprising fixed filter coefficients of the FIR filter. An adaptive noise shaping filter coupled between the low pass filter and the adaptive quantizer, the adaptive noise shaping filter to flatten the signal in the frequency spectrum corresponding to the frequency spectrum of the low pass filter. Configured,
26. The system of claim 25.   The adaptive noise shaping filter generates a signal indicating a filter coefficient of the adaptive noise shaping filter, and the signal indicating a filter coefficient of the adaptive noise shaping filter is included in a bit stream output to the decoder by the encoder The system according to claim 27,.   The encoder includes an encoding circuit configured to generate a codeword based on the quantized signal word generated by the adaptive quantizer, and the decoder is configured to generate the codeword generated by the encoding circuit. 26. The system of claim 25, comprising a decoding circuit configured to generate a quantized signal word based on.   30. The system of claim 29, wherein the encoding circuit and the decoding circuit are configured to use escape encoding. An input filter having the determined control parameters and configured to limit the bandwidth of the input signal to less than 75% of the available bandwidth based on the sampling frequency of the input signal;
And an encoder configured to generate a quantized signal based on the difference signal,
The encoder
An adaptive quantizer,
A system configured to generate a feedback signal, and comprising a feedback circuit having an inverse quantizer and a predictor circuit, said predictor circuit having control parameters determined based on the frequency response of said input filter . A decoder configured to decode the signal encoded by the encoder;
32. The system of claim 31.   The input filter is a low pass filter, the determined filter coefficients of the low pass filter are fixed filter coefficients of the low pass filter, the predictor circuit includes a finite impulse response (FIR) filter, and the predictor circuit 32. The system of claim 31, wherein the determined control parameter of comprises the fixed filter coefficients of the FIR filter.   The input filter is a band pass filter, the determined control parameters of the band pass filter are fixed filter coefficients of the band pass filter, the predictor circuit comprises a finite impulse response (FIR) filter, 32. The system of claim 31, wherein the determined control parameters of a predictor circuit include fixed filter coefficients of the FIR filter. Means for low pass filtering the input signal using the determined filtering parameters;
Means for generating a quantization signal based on the difference signal;
Means for generating a prediction signal based on the quantized signal using control parameters determined based on the frequency response of the low pass filtering means;
And means for generating the difference signal. Including means for decoding the encoded signal,
36. The system of claim 35.   The means for low pass filtering comprises a low pass filter with fixed filter coefficients, and the means for predicting comprises a finite impulse response (FIR) filter with fixed filter coefficients based on the filter coefficients of the low pass filter. The system described in. A device,
A decoder configured to generate a decoded signal based on the quantized signal, said decoder comprising
An inverse quantizer,
The apparatus further comprising:
An apparatus comprising a low pass filter having a determined filter coefficient and configured to receive an output of the decoder, the predictor circuit having control parameters determined based on a frequency response of the low pass filter.   The determined filter coefficients of the low pass filter are fixed filter coefficients of the low pass filter, the predictor circuit comprises a finite impulse response (FIR) filter, and the determined control parameters of the predictor circuit are: 39. The apparatus of claim 38, comprising fixed filter coefficients of the FIR filter. An inverse adaptive noise shaping filter coupled between the inverse quantizer and the low pass filter,
An apparatus according to claim 38.   41. The apparatus of claim 40, wherein the inverse adaptive noise shaping filter is configured to receive a signal that is included in a bit stream received by the decoder and that is indicative of inverse adaptive noise shaping filter coefficients.   39. The apparatus of claim 38, wherein the decoder comprises decoding circuitry configured to generate a quantized signal word based on a codeword in a bitstream received by the decoder. The decoding circuit
An escape code indicates that the bit stream contains a quantized signal word,
The escape code indicates the end of the signaling channel,
43. The apparatus of claim 42, wherein the escape code is configured to be responsive to at least one of: an end of a signal to be encoded.   43. The apparatus of claim 42, wherein the decoding circuit is configured to decode codewords in the bitstream using Huffman coding.   39. The apparatus of claim 38, wherein the dequantizer is a variable rate dequantizer. The inverse quantizer is
_{d n + 1 = βd n +} m (c n / L factor)
Are configured to control the step size, where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, m (C _n / L _factor ) is a logarithmic multiplier selected based on the current quantization signal c _n and the load factor L _factor , β is a leakage factor, and d _n +1 is the next quantized signal 39. The apparatus of claim 38 corresponding to a step size of the log domain applied to words c _{n + 1} . The inverse quantizer is
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
Are configured to control the step size, where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, m (C _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, and d _min is a threshold step size in the logarithmic domain The apparatus according to claim 38, wherein d _n +1 corresponds to the step size of the log domain applied to the next quantized signal word c _{n + 1} . Decoding the coded signal using a feedback loop, said decoding step
Dequantizing the quantized signal using an inverse quantizer;
Generating a prediction signal based on the quantized signal using a predictor circuit;
Filtering the decoded signal with a low pass filter having the determined filter coefficients, the predictor circuit having control parameters determined based on the frequency response of the low pass filter.   The determined filter coefficients of the low pass filter are fixed filter coefficients of the low pass filter, the predictor circuit comprises a finite impulse response (FIR) filter, and the determined control parameters of the predictor circuit are: 49. The method of claim 48, comprising fixed filter coefficients of the FIR filter.   50. The method of claim 49, wherein the filtering step comprises using an inverse adaptive noise shaping filter coupled between an output of the decoder and an input of the low pass filter. Setting a filter coefficient of the inverse adaptive noise shaping filter based on a signal included in a bit stream of the encoded signal.
51. The method of claim 50. Generating a quantized signal word based on a codeword included in the bit stream of the encoded signal,
49. The method of claim 48.   53. The method of claim 52, comprising using escape coding to generate the quantized signal word based on the codeword.   53. The method of claim 52, comprising decoding codewords in the bitstream using Huffman coding. The inverse quantizer is
_{d n + 1 = βd n +} m (c n / L factor)
Are configured to control the step size, where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, m (C _n / L _factor ) is a logarithmic multiplier selected based on the current quantization signal c _n and the load factor L _factor , β is a leakage factor, and d _n +1 is the next quantized signal 49. The method of claim 48, corresponding to the step size of the log domain applied to word c _{n + 1} . The inverse quantizer is
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
Are configured to control the step size, where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, m (C _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, and d _min is a threshold step size in the logarithmic domain 49. The method of claim 48, wherein d _n +1 corresponds to the step size of the log domain applied to the next quantized signal word c _{n +1} . A non-transitory computer readable medium having content for configuring signal processing circuitry to perform the method, the method comprising:
Decoding the encoded signal using feedback, said decoding step
Dequantizing the quantized signal;
Generating a prediction signal based on the quantized signal;
Filtering the decoded signal, wherein the filtering includes low pass filtering using the determined filter coefficients, and wherein the generating of the prediction signal is based on a frequency response of the low pass filtering. A non-transitory computer readable medium, comprising using the control parameters determined.   The determined filter coefficient is a fixed filter coefficient of a low pass filter, the predictor signal is generated using a finite impulse response (FIR) filter, and the determined control parameter is a fixed filter of the FIR filter 58. The non-transitory computer readable medium of claim 57, comprising a coefficient.   58. The non-transitory computer readable medium of claim 57, wherein the filtering step comprises applying inverse adaptive noise shaping filtering to the decoded signal. The method is
58. The non-transitory computer readable medium of claim 57, comprising generating a quantized signal word based on a codeword included in a bit stream of the encoded signal. Including a decoder configured to generate a decoded signal based on the quantized signal,
The decoder
An inverse quantizer,
A predictor circuit,
An encoder, the encoder having a determined filter coefficient, and including a low pass filter configured to filter the signal to be encoded by the encoder, the predictor circuit of the decoder comprising A system having control parameters determined based on a frequency response of the low pass filter of the encoder.   The determined filter coefficients of the low pass filter are fixed filter coefficients of the low pass filter, the predictor circuit comprises a finite impulse response (FIR) filter, and the determined control parameters of the predictor circuit are: 62. The system of claim 61, comprising fixed filter coefficients of the FIR filter. An inverse adaptive noise shaping filter coupled to the output of the inverse quantizer of the decoder;
62. The system of claim 61.   64. The system of claim 63, wherein the inverse adaptive noise shaping filter is configured to apply filter coefficients based on a synchronization signal included in a bit stream received by the decoder.   62. The system of claim 61, wherein the decoder comprises decoding circuitry configured to generate a quantized signal word based on a codeword in the bit stream received by the decoder from the encoder. A system,
Including a decoder configured to generate a decoded signal based on the quantized signal,
The decoder
An inverse quantizer,
A predictor circuit, the system further coupled to the decoder, and based on the sampling frequency of the quantized signal to limit the bandwidth of the output of the decoder to less than 75% of the available bandwidth A system, comprising: an configured output filter, wherein the predictor circuit has control parameters determined based on a frequency response of the output filter.   67. The system of claim 66, comprising an encoder configured to generate an encoded signal.   The output filter is a low pass filter, the determined filter coefficients of the low pass filter are fixed filter coefficients of the low pass filter, the predictor circuit includes a finite impulse response (FIR) filter, and the predictor circuit 67. The system of claim 66, wherein the determined control parameter of comprises the fixed filter coefficients of the FIR filter.   The output filter is a band pass filter, the determined control parameters of the band pass filter are fixed filter coefficients of the band pass filter, the predictor circuit comprises a finite impulse response (FIR) filter, 67. The system of claim 66, wherein the determined control parameters of a predictor circuit include fixed filter coefficients of the FIR filter. A system,
A decoder configured to generate a decoded signal based on the quantized signal,
The decoder
An inverse quantizer,
The system further comprising:
A system, comprising: an output filter configured to filter an output of the decoder, the predictor circuit having control parameters determined based on a frequency response of an encoder low pass filter.   71. The system of claim 70, comprising an encoder that includes the encoder low pass filter.   71. The system of claim 70, wherein the predictor circuit comprises a finite impulse response (FIR) filter, and the determined control parameters of the predictor circuit comprise fixed filter coefficients of the FIR filter. An inverse adaptive noise shaping filter coupled to the output of the inverse quantizer of the decoder;
71. The system of claim 70. A system,
Means for dequantizing the quantized signal;
Means for generating a prediction signal based on the quantized signal, wherein the means for generating the prediction signal uses control parameters determined based on a frequency response of an encoder low pass filter, the system further comprising:
Means for generating a decoded signal based on the quantized signal and the predicted signal;
And means for filtering the decoded signal.   75. The system of claim 74, comprising an encoder that includes the encoder low pass filter. Means for recovering the frequency spectrum of the decoded signal,
75. The system of claim 74. A device,
An input filter configured to filter an input signal and having an upper edge frequency;
An adaptive noise shaping filter configured to flatten a filtered signal below a threshold frequency range based on the upper edge frequency;
An encoder coupled to the adaptive noise shaping filter, wherein the encoder is configured to generate a quantized signal based on the differential signal;
The encoder
An adaptive quantizer,
An apparatus, configured to generate a feedback signal, and comprising a decoder comprising an inverse quantizer and a predictor circuit, said predictor circuit having control parameters determined based on said threshold frequency range.   78. The apparatus of claim 77, wherein the predictor circuit comprises a finite impulse response (FIR) filter, and wherein the determined control parameter comprises fixed filter coefficients of the FIR filter.   78. The apparatus of claim 77, wherein the adaptive noise shaping filter is configured to generate a signal indicative of filter coefficients of the adaptive noise shaping filter.   78. The apparatus of claim 77, wherein the encoder comprises encoding circuitry configured to generate a codeword based on the quantized signal word generated by the adaptive quantizer. The coding circuit
The quantized signal word is not associated with the corresponding encoded codeword,
81. The apparatus of claim 80, configured to generate an escape code in response to at least one of an end of a signaling channel and an end of a signal to be encoded.   81. The apparatus of claim 80, wherein the encoding circuit is configured to generate the codewords using Huffman coding.   78. The apparatus of claim 77, wherein the adaptive quantizer is a variable rate quantizer. The adaptive quantizer is
_{d n + 1 = βd n +} m (c n / L factor)
Are configured to control the quantization step size, where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, and L _factor is the loading factor , M (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, and d _n +1 is the following quantum 84. Apparatus according to claim 83, corresponding to the step size of the log domain applied to the signal word c _{n + 1} . The adaptive quantizer is
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
Are configured to control the quantization step size, where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, and L _factor is the loading factor , M (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, and d _min is a threshold value in the logarithmic domain 84. The apparatus of claim 83, wherein a step size, d _n +1 corresponds to the step size of the log domain applied to the next quantized signal word c _{n +1} . The input filter is
78. The apparatus of claim 77, comprising one of a low pass filter and a band pass filter. Filtering the input signal to remove components above the cutoff frequency;
Applying adaptive noise shaping to the filtered input signal to flatten signal components in the filtered input signal below a threshold frequency range;
Encoding the noise shaped signal.
The encoding step
Generating a quantization signal based on the difference signal;
Generating a feedback signal using a predictor circuit, the predictor circuit having control parameters determined based on the threshold frequency range. Generating a signal indicative of filter coefficients used to apply said adaptive noise shaping,
89. The method of claim 87. Generating a codeword based on the quantized signal word,
89. The method of claim 87. Including the steps of using escape encoding,
90. The method of claim 89. Let the quantization step size be
_{d n + 1 = βd n +} m (c n / L factor)
And c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, and m (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, and d _n +1 is applied to the next quantized signal word c _{n +1} 90. A method according to claim 87, corresponding to the step size of the log domain being Let the quantization step size be
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
And c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, and m (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, d _min is a threshold step size in the logarithmic domain, d _n 89. The method of claim 87, wherein +1 corresponds to the step size of the log domain applied to the next quantized signal word c _{n +1} . The encoding step
89. The method of claim 87, comprising generating the difference signal based on the feedback signal and the noise shaping signal. The step of filtering the input signal comprises:
90. The method of claim 87, including low pass filtering and one of band pass filters. A non-transitory computer readable medium having content constituting signal processing circuitry to perform the method, the method comprising:
Filtering the input signal to remove components above the cutoff frequency;
Applying adaptive noise shaping to the filtered input signal to flatten signal components in the input signal below a threshold frequency range;
Encoding the noise shaped signal.
The encoding step
Generating a quantization signal based on the difference signal;
Generating a prediction signal using control parameters determined based on the threshold frequency range. The method is
96. The non-transitory computer readable medium of claim 95, comprising generating a signal indicative of filter coefficients used to apply the adaptive noise shaping. The method is
96. The non-transitory computer readable medium of claim 95, comprising generating a codeword based on a quantized signal word. The method is
100. The non-transitory computer readable medium of claim 97, comprising using escape coding. The method comprises quantization step size
_{d n + 1 = βd n +} m (c n / L factor)
And c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, and m (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, and d _n +1 is applied to the next quantized signal word c _{n +1} 99. The non-transitory computer readable medium of claim 98, corresponding to a step size of the log domain being The method comprises quantization step size
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
And c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, and m (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, d _min is a threshold step size in the logarithmic domain, d _n 99. The non-transitory computer readable medium of claim 98, wherein +1 corresponds to the step size of the log domain applied to the next quantized signal word c _{n +1} . The step of filtering the input signal comprises:
96. The non-transitory computer readable medium of claim 95, including one of low pass filtering and band pass filtering. A system,
Means for removing frequency components in the input signal above the cutoff frequency;
Means for applying adaptive noise shaping to the output of the removal means for flattening signal components below the threshold frequency range;
Means for generating a quantization signal based on the difference signal;
Means for generating a prediction signal using control parameters determined based on said threshold frequency range. Means for transmitting a signal indicative of the filter coefficients of the means for applying the adaptive noise shaping,
A system according to claim 102. Means for generating a codeword based on the quantized signal word,
A system according to claim 102.   105. The system of claim 104, wherein the means for removing frequency components comprises a low pass filter. Including means for decoding the encoded signal,
A system according to claim 102. A device,
A decoder configured to generate a decoded signal based on the quantized signal representing the encoded signal, the decoder comprising:
An inverse quantizer,
The apparatus further comprising: a finite impulse response (FIR) filter;
The inverse adaptive noise shaping filter configured to receive a control signal included in a bitstream including the encoded signal, the control signal flattening signal components below a threshold frequency range of the encoded signal. The adaptive noise shaping applied to the
An apparatus comprising an output filter configured to filter an inverse noise shaped signal and having an upper edge frequency.   108. The apparatus of claim 107, wherein the decoder comprises decoding circuitry configured to generate a quantized signal word based on a codeword in the bitstream. The decoding circuit
An escape code indicates that the bit stream contains a quantized signal word,
The escape code indicates the end of the signaling channel,
109. The apparatus of claim 108, wherein the escape code is configured to be responsive to at least one of: an end of a signal to be encoded.   109. The apparatus of claim 108, wherein the decoding circuit is configured to decode codewords in the bitstream using Huffman coding.   109. The apparatus of claim 108, wherein the dequantizer is a variable rate dequantizer. The inverse quantizer is
_{d n + 1 = βd n +} m (c n / L factor)
Are configured to control the step size, where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, m (C _n / L _factor ) is a logarithmic multiplier selected based on the current quantization signal c _n and the load factor L _factor , β is a leakage factor, and d _n +1 is the next quantized signal 112. Apparatus according to claim 111, corresponding to the step size of the log domain applied to words c _{n +1} . The inverse quantizer is
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
Are configured to control the step size, where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, m (C _n / L _factor ) is a logarithmic multiplier selected based on the current quantization signal c _n n and the load factor L _factor , β is a leakage factor, and d _min is a threshold step in the logarithmic domain in size, d n ₊₁ corresponds to the step size of the logarithmic region to be applied to the next quantized signal word c _{n + 1,} apparatus according to claim 111. Method,
Decoding the quantized signal representing the coded signal, said decoding step
Dequantizing the quantized signal using an inverse quantizer;
Generating a prediction signal using a predictor circuit, the method further comprising:
Applying inverse adaptive noise shaping to the decoded quantized signal based on a control signal indicating adaptive noise shaping applied to flatten signal components below a threshold frequency range of the encoded signal;
Filtering the inverse noise shaped signal to remove components above the cut-off frequency. Generating a quantized signal word based on the codewords in the bit stream indicative of the encoded signal;
117. The method of claim 114. Using escape coding to decode the code word,
116. The method of claim 115.   116. The method of claim 115, wherein the filtering the inverse noise shaped signal comprises low pass filtering the inverse noise shaped signal. A non-transitory computer readable medium having content constituting signal processing circuitry to perform the method
The method comprises the steps of decoding a quantized signal representative of the encoded signal,
The decoding step
Dequantizing the quantized signal;
Generating a prediction signal,
The method further includes inverse adaptive noise shaping on the decoded quantized signal based on a control signal indicative of adaptive noise shaping applied to flatten signal components below a threshold frequency range of the encoded signal. Applying step,
Filtering the inverse noise shaping signal to remove components above the cut-off frequency. The method is
119. The non-transitory computer readable medium of claim 118, comprising generating a quantized signal word based on a codeword in a bit stream indicative of the encoded signal. The method is
120. The non-transitory computer readable medium of claim 119, comprising using escape coding to decode the codeword. The step of filtering the inverse noise shaping signal
120. The non-transitory computer readable medium of claim 119, comprising low pass filtering the inverse noise shaped signal. Means for dequantizing a quantized signal representative of the encoded signal;
Means for generating a prediction signal;
Means for generating a decoded signal based on the dequantized signal and the predicted signal;
Means for applying inverse adaptive noise shaping to the decoded signal based on a control signal indicative of adaptive noise shaping applied to flatten signal components below the threshold frequency range in the encoded signal;
And means for removing components above the cut-off frequency in the inverse noise shaped signal. Means for generating a quantized signal word based on codewords in a bitstream representing the encoded signal,
124. The system of claim 122. The removal means is
124. The system of claim 122, comprising a low pass filter. A device,
An encoder configured to generate a quantized signal word based on the differential signal,
The encoder
A step size, including an adaptive quantizer, applied by the adaptive quantizer is generated in a feedback loop based on the loading factor and the quantized signal word generated by the adaptive quantizer.
The encoder further includes a decoder configured to generate a prediction signal and having an inverse quantizer and a predictor circuit,
The apparatus further comprises an encoding circuit configured to generate a codeword based on the quantized signal word generated by the adaptive quantizer, the encoding circuit corresponding to the encoded codeword. An apparatus configured to generate an escape code in response to an unrelated quantization signal word. The coding circuit
126. The apparatus of claim 125, configured to generate an escape code in response to at least one of an end of a signaling channel and an end of a signal to be encoded.   126. The apparatus of claim 125, wherein the encoding circuit is configured to generate the codeword using Huffman coding. The feedback loop is
_{d n + 1 = βd n +} m (c n / L factor)
Are configured to generate the step size, where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, and L _factor is the loading factor , M (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, and d _n +1 is the following quantum 126. Apparatus according to claim 125, corresponding to the step size of the log domain applied to the signal word c _{n + 1} . The feedback loop is
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
Are configured to generate the step size, where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, and L _factor is the loading factor , M (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, and d _min is a threshold value in the logarithmic domain 126. The apparatus of claim 125, which is a step size and d _n +1 corresponds to the step size of the log domain to be applied to the next quantized signal word c _{n +1} . Method,
Encoding the signal, the encoding step comprising
Generating a quantization signal word based on the difference signal, wherein a quantization step size is determined in a feedback loop based on a loading factor and the generated quantization signal word,
Generating a prediction signal based on the generated quantization signal word;
Generating the difference signal based on the signal to be encoded and the prediction signal;
Generating a codeword based on the quantized signal word, wherein generating the codeword is responsive to a quantized signal word not associated with a corresponding encoded codeword to generate an escape code. Method, including. The end of the signal channel of the signal to be coded, and the end of the signal to be coded,
Generating an escape code in response to at least one of
131. The method of claim 130. Generating the codeword using Huffman coding,
131. The method of claim 130. The quantization step size is
_{d n + 1 = βd n +} m (c n / L factor)
And c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, and m (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, and d _n +1 is the next quantized signal word c _{n +1} Corresponding to the step size of the applied log domain
131. The method of claim 130. The quantization step size is
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
And c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the loading factor, and m (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, d _min is a threshold step size in the logarithmic domain, d _n +1 corresponds to the step size of the log domain applied to the next quantized signal word c _{n +1} ,
131. The method of claim 130. A non-transitory computer readable medium having content for configuring a signal processing circuit to encode a signal, said encoding being:
Generating a quantized signal word based on the differential signal, wherein a quantizer step size is determined in a feedback loop based on a loading factor and the generated quantized signal word.
Generating a prediction signal based on the generated quantization signal word;
Generating the difference signal based on the signal to be encoded and the prediction signal;
Generating a codeword based on the quantized signal word, wherein generating the codeword generates an escape code in response to a quantized signal word not associated with a corresponding encoded codeword. Non-transitory computer readable media, including: The encoding is
The end of the signal channel of the signal to be coded, and the end of the signal to be coded,
136. The non-transitory computer readable medium of claim 135, comprising generating an escape code in response to at least one of. The encoding is
136. The non-transitory computer readable medium of claim 135, comprising generating codewords using Huffman coding. The encoding is
_{d n + 1 = βd n +} m (c n / L factor)
Determining the quantization step size according to where c _n is the current quantization signal word, d _n corresponds to the current step size in the logarithmic domain, and L _factor is the loading factor , M (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, and d _n +1 is the following quantum Corresponding to the step size of the log domain applied to the quantization signal word c _{n + 1} ,
136. The non-transitory computer readable medium of claim 135. The encoding is
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
Determining the quantization step size according to where c _n is the current quantization signal word, d _n corresponds to the current step size in the logarithmic domain, and L _factor is the loading factor , M (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, and d _min is a threshold value in the logarithmic domain The step size, d _n +1 corresponds to the step size of the log domain applied to the next quantized signal word c _{n +1} ,
136. The non-transitory computer readable medium of claim 135. A system,
Means for generating a quantization signal word based on the difference signal, the quantization step size being determined based on a loading factor and the generated quantization signal word;
Means for generating a prediction signal based on the generated quantization signal word;
Means for generating the difference signal based on the signal to be encoded and the prediction signal;
Means for generating a codeword based on the quantized signal word, wherein generating the codeword is responsive to a quantized signal word not associated with a corresponding encoded codeword to generate an escape code. Including the system. The means for generating a codeword is
141. The system of claim 140, generating an escape code in response to at least one of: an end of a signal channel of the signal to be encoded; and an end of the signal to be encoded.   141. The system of claim 140, wherein the means for generating a codeword generates the codeword using Huffman coding. The means for generating a quantized signal word comprises
_{d n + 1 = βd n +} m (c n / L factor)
Determine the quantization step size according to where c _n is the current quantization signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the load factor, m ( c _n / L _factor ) is a logarithmic multiplier selected based on the current quantization signal c _n and the load factor L _factor , β is a leakage factor, and d _n +1 is the next quantized signal word 141. The system of claim 140 corresponding to the step size of the log domain applied to c _{n +1} . The means for generating a quantized signal word comprises
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
Determine the quantization step size according to where c _n is the current quantization signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the load factor, m ( c _n / L _factor ) is a logarithmic multiplier selected based on the current quantization signal c _n and the load factor L _factor , β is a leakage factor, and d _min is a threshold step size in the logarithmic domain 141. The system of claim 140, wherein d _n +1 corresponds to the step size of the log domain to be applied to the next quantized signal word c _{n +1} . Including means for decoding the codeword generated by the means for generating the codeword,
141. The system of claim 140. A device,
A decoding circuit configured to generate a quantized signal word based on a codeword included in a bitstream, the escape code in the bitstream indicating that the quantized signal word is included in the bitstream. A decoding circuit, configured to respond
An inverse quantizer, wherein the step size applied by the inverse quantizer is generated in a feedback loop and based on the load factor and the quantization signal word received by the inverse quantizer from the decoding circuit The inverse quantizer,
A predictor circuit coupled to the inverse quantizer. The coding circuit
147. The apparatus of claim 146, configured to be responsive to at least one of an escape code indicating an end of a signal channel and an escape code indicating an end of a signal to be encoded.   25. The apparatus of claim 24, wherein the encoding circuit is configured to generate the quantized signal word using Huffman coding. The feedback loop is
_{d n + 1 = dn + m} (c n / L factor)
Are configured to generate the step size, where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, and L _factor is the loading factor , M (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, and d _n +1 is the following quantum 147. Apparatus according to claim 146, corresponding to the step size of the logarithmic domain applied to the signal word c _{n + 1} . The feedback loop is
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
Are configured to generate the step size, where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, and L _factor is the loading factor , M (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leakage factor, and d _min is a threshold value in the logarithmic domain 147. The apparatus of claim 146, wherein a step size, d _n +1 corresponds to the step size of the log domain to be applied to the next quantized signal word c _{n +1} . Method,
Generating a quantized signal word based on a codeword included in the bitstream, the method comprising: responding to an escape code in the bitstream indicating that a quantized signal word is included in the bitstream. And dequantizing the generated quantized signal word, wherein a step size applied in the inverse quantization step is based on a load factor and the generated quantized signal word in a feedback loop. Step to be determined
Generating a prediction signal based on the generated quantized signal word. The step of generating the quantized signal word comprises:
152. The method of claim 151, comprising the step of responding to at least one of an escape code indicating an end of a signaling channel and an escape code indicating an end of a signal to be encoded.   152. The method of claim 151, wherein generating the quantized signal word comprises using Huffman coding. The feedback loop is
_{d n + 1 = βd n +} m (c n / L factor)
Determine the step size according to where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the load factor, m (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantization signal c _n and the load factor L _factor , β d _n is a leakage factor, and d _n +1 is the next quantized signal word 152. The method of claim 151, corresponding to a step size of the log domain applied to c _{n +1} . The feedback loop is
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
Determine the step size according to where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the load factor, m (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantization signal c _n and the load factor L _factor , β is a leakage factor, and d _min is a threshold step size in the logarithmic domain 154. The method of claim 151, wherein d _n +1 corresponds to the step size of the log domain applied to the next quantized signal word c _{n +1} . A non-transitory computer readable medium having content for configuring a signal processing circuit to decode a signal, said decoding comprising
Generating a quantized signal word based on a codeword included in the bitstream, comprising: responding to an escape code in the bitstream indicating that the quantized signal word is included in the bitstream. Generating and
Dequantizing the generated quantized signal word, wherein a step size applied in the inverse quantization step is determined in a feedback loop based on a loading factor and the generated quantized signal word Inverse quantization, and
Generating a prediction signal based on the generated quantized signal word. Generating the quantized signal word is
157. The non-transitory computer readable medium of claim 156, comprising responding to at least one of an escape code indicating an end of a signal channel and an escape code indicating an end of a signal to be encoded.   157. The non-transitory computer readable medium of claim 156, wherein generating the quantized signal word comprises using Huffman coding. The feedback loop is
_{d n + 1 = βd n +} m (c n / L factor)
Determine the step size according to where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the load factor, m (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantization signal c _n and the load factor L _factor , β d _n is a leakage factor, and d _n +1 is the next quantized signal word 157. The non-transitory computer readable medium of claim 156 corresponding to a step size of the log domain applied to c _{n +1} . The feedback loop is
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
Determine the step size according to where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the load factor, m (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantization signal c _n and the load factor L _factor , β is a leakage factor, and d _min is a threshold step size in the logarithmic domain 156. The non-transitory computer readable medium of claim 156, wherein d _n +1 corresponds to the step size of the log domain applied to the next quantized signal word c _{n +1} . A system,
Means for generating a quantized signal word based on a codeword contained in the bitstream, wherein said generation of a quantized signal word indicates that a quantized signal word is included in the bitstream. Means for responding to an escape code and means for dequantizing the generated quantized signal word, wherein a step size applied in the dequantization is a load factor and the generation in a feedback loop. Means determined based on the quantized quantization signal word;
Means for generating a prediction signal based on the generated quantization signal word. Generating the quantized signal word is
162. The system of claim 161, comprising responding to at least one of an escape code indicating an end of a signaling channel and an escape code indicating an end of a signal to be encoded.   162. The system of claim 161, wherein generating the quantized signal word comprises using Huffman coding. The feedback loop is
_{d n + 1 = βd n +} m (c n / L factor)
Determine the step size according to where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the load factor, m (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantized signal c _n and the load factor L _factor , β is a leak factor, and d _n +1 is the next quantized signal word c _162. The system of claim 161, corresponding to the step size of the log domain applied to _{n + 1} . The feedback loop is
d _{n + 1} = max (β d _n + m (c _n / L _factor ), d _min )
Determine the step size according to where c _n is the current quantized signal word, d _n corresponds to the current step size in the logarithmic domain, L _factor is the load factor, m (c _n / L _factor ) is a logarithmic multiplier selected based on the current quantization signal c _n and the load factor L _factor , β is a leakage factor, and d _min is a threshold step size in the logarithmic domain , D _n +1 correspond to the step size of the log domain to be applied to the next quantized signal word c _{n +1} . Means for generating a decoded signal based on the dequantized signal word and the predicted signal,
162. The system of claim 161.

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