JPH03278621A - Noise reduction circuit - Google Patents

Abstract

PURPOSE:To expand a noise control range and to apply noise control over a wide reception input range by using fuzzy control so as to apply feedback control. CONSTITUTION:A fuzzy control means 14 applies fuzzy deduction processing according to a fuzzy production rule given by a membership function as to each signal according to the input condition of a reception electric field strength from an input level detection circuit 12 and a noise level detection value from an output noise level detection circuit 13. A fuzzy control signal generating circuit 15 generates a fuzzy control signal based on a noise level detection detected by the output noise level detection circuit 13 and a final deduction result generated from the fuzzy deduction means 14, to control the noise reduction of the noise reduction means 11. Thus, it is possible to expand the noise control range and to apply excellent noise reduction over a wide reception input range.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a noise reduction circuit that reduces various noises contained in a received input using fuzzy control.

[Prior Art] There are various methods for reducing the noise level of each noise included in the received input, and there is a noise reduction circuit using feedback control as shown in FIG.

In FIG. 5, 20 is an overall noise reduction circuit that performs processing to reduce various noises included in reception inputs such as AM and FM broadcasting, and internally includes a noise reduction means 21, an output noise detection circuit 22, and a noise control circuit. A signal generation circuit 23 is provided.

The noise reduction means 21 includes, for example, a frequency characteristic control circuit, a separation control circuit, a muting control circuit, etc., or a combination thereof, and operates each of these circuits to reduce the noise contained in the receiving input. Performs processing to reduce various types of noise.

The output noise detection circuit 22 detects the noise level included in the output signal after the noise reduction processing by the noise reduction means 21, and generates a noise level detection signal.

Noise control signal generation times! 23 is an output noise detection and generation circuit 220 that compares the generated noise level detection signal with a fixed reference voltage Vs, generates a noise control signal proportional to the difference, and feeds it back to the noise reduction means 21. By performing the control, noise generated on the output side of the receiver can be effectively removed and a high quality audio signal can be reproduced.

[Problems to be Solved by the Invention] As mentioned above, the conventional receiver noise reduction circuit using feedback control compares the noise level detection value on the output side with a fixed reference voltage to determine the noise level for feedback control. It was generating an operation control signal.

When noise is controlled by such feedback control, the noise level is maintained at the level of the reference voltage Vs as shown in FIG. 6 within the range of the control limit value of the noise reduction circuit, so the noise is effectively reduced. Is possible.

However, when the control limit range of this noise reduction circuit is exceeded, noise control becomes impossible and the noise level rapidly increases as shown in the figure. For this reason, the conventional noise reduction circuit using feedback control has a problem in that when the range of the control limit value of the noise reduction circuit is narrow, the noise control range seen from the received input level becomes narrow.

Particularly in FM receivers, noise reduction circuits such as frequency characteristic control circuits, separation control circuits, muting control circuits, etc. have narrow control limit ranges (for example, approximately 20 dB for separation control circuits, and approximately 20 dB for frequency characteristic control circuits). (several dB), the noise control range seen from the receiver's power level becomes narrower, and the noise control characteristics become steeper.

When the noise control range becomes narrow and the noise control characteristics become steep,
In a reception environment where the reception input level fluctuates greatly, such as in a receiver installed in a car, the noise reduction circuit does not work well and the noise level fluctuates widely (which causes the inconvenience of not being able to receive good reception). there were.

[Purpose of the invention]

The present invention has been made to solve the above-mentioned problems, and by performing feedback control using fuzzy control, the noise control range can be expanded and noise control can be performed over a wide receiving input range. The purpose of the present invention is to provide an improved noise reduction circuit.

〔overview〕

Regarding a noise reduction circuit that uses fuzzy control to reduce various noises included in a reception input, there is provided a noise reduction means for controlling the reduction of noise components in the reception input, and an input level detection unit for detecting a received electric field strength value of the reception input. an output noise level detection circuit that detects a noise level included in the output signal after noise reduction processing by the noise reduction means;
A fuzzy inference method uses the received electric field strength value detected by the input level detection circuit and the noise level detection value detected by the output noise level detection circuit as input conditions, and performs fuzzy inference using a fuzzy production rule given by a membership function for each detection value. A fuzzy control signal generation circuit that controls the noise reduction operation performed by the noise reduction means based on the noise level detection value detected by the output noise level detection circuit and the inference result of the fuzzy inference means. As a result, the noise control range of the noise reduction circuit is expanded, noise control is performed over a wide reception input range, and high-quality reception can be performed.

[Means to solve the problem]

The means adopted by the present invention to solve the above-mentioned problems are as follows:
This will be explained with reference to FIG. FIG. 1 is a block diagram showing the basic configuration of the present invention.

In FIG. 1, 10 is the entire noise reduction circuit. Reference numeral 11 denotes a noise reduction means, which is composed of, for example, a frequency characteristic control circuit, a separation control circuit, a muting control circuit, etc., or a combination thereof, and operates each of these circuits to reduce the noise contained in the reception input. Performs processing to reduce various types of noise.

Reference numeral 12 denotes an input level detection circuit, which performs a process of detecting a received field strength value E of received input.

Reference numeral 13 denotes an output noise level detection circuit, which detects the noise level included in the output signal after the noise reduction processing by the noise reduction means 11 and outputs a noise level detection signal.

14 is a fuzzy control means, and input level detection circuit 1
Using the received electric field strength ME from 2 and the noise signal from the output noise level detection circuit as input conditions, fuzzy inference is performed using fuzzy production rules given by membership functions for each of the signals.

Reference numeral 15 denotes a fuzzy control signal generation circuit, which generates a fuzzy control signal for controlling the operation of the noise reduction circuit 11 based on the noise level detection value detected by the output noise level detection circuit 13 and the inference result of the fuzzy inference means 14. I do.

[Effect]

The operation of the present invention will be explained with reference to FIG.

FIG. 2 illustrates an example of fuzzy inference processing used in the present invention.

The input level detection circuit 12 detects the received field strength value E of the received input and sends it to the fuzzy inference means 14.

The output noise level detection circuit 13 includes the noise reduction means 11
The noise level included in the output signal after the noise reduction processing is detected and sent to the fuzzy inference means 14.

The fuzzy control means 14 uses the received electric field strength value E from the input level detection circuit 12 and the noise level detection value from the output noise level detection circuit as input conditions, and according to the fuzzy production rule given by the membership function for each signal. , performs fuzzy inference as shown in FIG.

As fuzzy production rules in this case, for example, the following fuzzy production rules R1 and R2 are used.

(1) Fuzzy production rule R1 ■ Preconditions (
IF): aI: Received electric field level is high.

bl: Low noise level.

■Result (consequent part, THEN): Decrease the control time constant, which is a controlled variable.

(2) Fuzzy production rule R2 ■ Preconditions (
IF): a2: Received electric field level is low.

b2: The noise level is high.

■Result (consequent part, THEN): The reference voltage Vs, which is the inference result, is decreased.

In Fig. 2, mA and mB+ are the received electric field strength value E and the noise level detection value N, which are input vector elements.
These are the membership functions regarding the antecedent part of the fuzzy production rule R1 for . mA, and mB
z is a fuzzy production rule R for the received field strength value E and noise level detection value N, which are input conditions.
These are the membership functions regarding the antecedent part of No. 2.

Furthermore, mP and mHz are membership functions for the results (consequent parts) of the fuzzy production rules R1 and R2.

Each of these membership functions is theoretically or experimentally set in advance for each fuzzy production rule regarding the received electric field strength value E and noise level detection value N, which are input conditions, but the contents are explained in the example. This will be explained in the section below.

The fuzzy inference means 14 calculates the received electric field strength value E and the noise level detection value N, which are each observed input condition.
By performing fuzzy inference based on the membership functions of the antecedents of the corresponding fuzzy production rules R1 and R2, first, the membership functions mP+ and mP2 are determined as shown in FIGS. 2(C) and (f). Inference results for (each membership function mP and mP,
(shaded area) is calculated.

Next, the fuzzy inference means 14 calculates a membership function mPo as shown in FIG. A process is performed to obtain the reference voltage Vs of the final inference result. (The details of each of the above membership functions and each inference processing method based on them will be explained in the Examples section.) By each of the above inference processing, the received electric field strength value E becomes large.
As the noise level detection value N becomes smaller, that is, as the reception condition becomes better, the level of the reference voltage Vs, which is the final inference result, becomes smaller, and conversely, the received electric field strength value E becomes smaller.
The larger the noise level detection value N becomes, that is, the worse the reception condition becomes, the higher the level of the reference voltage Vs as the final inference result becomes.

The fuzzy control signal generation circuit 15 performs fuzzy control to control the operation of the noise reduction means 11 based on the noise level detection value detected by the output noise level detection circuit 13 and the reference voltage Vs of the final inference result generated by the fuzzy inference means 14. A signal is generated to control the noise reduction operation performed by the noise reduction means 11.

As a result, the higher the received electric field strength value E and the lower the detected noise level value N, that is, the better the reception condition, the lower the level of the reference voltage Vs, so the fuzzy control signal level is lowered and the noise reduction means 11 performs a noise reduction operation at a low reference voltage level.

Conversely, as the received electric field strength (L!E) becomes smaller and the detected noise level value N becomes larger, that is, as the reception condition worsens, the level of the reference voltage S increases, so the fuzzy control signal level increases. The noise reduction means 11 performs a noise reduction operation when the reference voltage level is high.

FIG. 3(a) shows the noise characteristics of the present invention in which fuzzy control is used in the feedback loop of the noise reduction circuit 11. Further, FIG. 6(t)) shows the noise characteristics of the conventional noise reduction circuit shown in FIG. 6 for reference.

In FIG. 3(a), the horizontal axis shows the amount of decrease in the received electric field strength value E, and the vertical axis shows the noise level. 2 shows the noise characteristics without fuzzy control, and 2 shows the noise characteristics with fuzzy control.

When performing fuzzy control as in the present invention, the larger the received electric field strength value E and the smaller the detected noise level value N, that is, the better the reception condition, the more fuzzy inference based on the fuzzy production rule R1 becomes the main focus. The level of the reference voltage (Vs) based on the final inference result is lowered, and low-level noise is also effectively removed.

On the other hand, as the received electric field strength value E becomes smaller and the detected noise level value N becomes larger, that is, as the reception condition becomes worse, the main body of the fuzzy inference processing changes the center of gravity of the inference result from the fuzzy production rule R1 to the inference based on the fuzzy production rule R2. or move on. As the inference results change, the reference voltage also changes from Vs to Vs2.

As a result, as shown in the figure, the noise characteristics become gentler than those without fuzzy control, and as is clear from the comparison with FIG. It increases significantly more than the circuit.

By using fuzzy control in the feedback loop of the noise reduction means 11 in this way, it is possible to achieve both a noise reduction effect and reproduction of a good quality audio signal.

That is, since noise reduction is performed by deleting or processing a part of the received signal, there is an antinomic relationship between the noise reduction effect and the quality of the reproduced audio signal.

However, in the present invention, the received electric field strength value E is large;
The smaller the noise level detection value N is, that is, the better the reception condition is, the lower the fuzzy control signal level is, so the less deletion or processing of the received signal by the noise reduction means 11 is performed, and a high quality audio signal is reproduced. be able to.

On the other hand, the received electric field strength value E is small and the noise level detection (
+! As N becomes larger, that is, as the reception condition worsens, the fuzzy control signal level increases and the noise reduction means 1
Since the noise reduction operation in step 1 is increased, when the reception condition is poor, the noise reduction means 11 can effectively remove high-level noise, thereby preventing a deterioration in the quality of the reproduced audio signal and malfunctions due to noise. can do.

As described above, the present invention performs fuzzy control on the noise reduction operation of the noise reduction circuit in the receiver, so it is possible to increase the noise control range and perform good noise reduction over a wide receiving input range. It became.

Furthermore, it is possible to skillfully achieve both improvement in the noise reduction effect and reproduction of audio signals of good quality.

Next, the stability of the noise reduction circuit using fuzzy control according to the present invention will be explained.

In FIG. 1, the noise reduction means IJ, the output noise level detection circuit 13, the fuzzy inference means 14, and the fuzzy control signal generation circuit 15 form a feedback loop.

By the way, a feedback loop is generally stable when it is a negative feedback loop, but becomes unstable and oscillates when it becomes a positive feedback loop. Therefore, the control range of the noise reduction operation is determined based on the conditions under which no positive feedback loop occurs.

In FIG. 1, among the components of the feedback loop, all circuits other than the fuzzy inference means 14 have a directionality of output relative to the input of the circuit operation that is uniquely defined, and the stability conditions thereof are well known. There is.

Therefore, in general terms, when the feedback loop by each other circuit is stable, the fuzzy inference means 14
If the fuzzy inference process does not change the direction between the input conditions and the final inference result, the entire feedback loop can be said to be stable.

Now, the fuzzy production rule R in Figure 2 mentioned above
Consider the polarity of control in the case of 1.

Now, if we set C - control amount E, received electric field strength value N - noise level, then C = f, (E, N) f - control amount function a C7a
E-θf(S)/c? s<0θC/θN=θf(N)/
θN>0, ----------(1).

Similarly, when considering the aforementioned fuzzy production rule R2, θC/δE−<OθC/θN −> 0−(2).

From these equations (1) and (2), if each rule is like the fuzzy production rules R1 and R2, the fuzzy inference means 14 determines the control polarity between the input condition and the final inference result by its fuzzy inference processing. It can be seen that there is no change in . Therefore, it is concluded that the entire feedback loop is stable.

〔Example〕

An embodiment of the present invention will be described with reference to FIGS. 2 to 4. FIG. 4 is an explanatory diagram of the configuration of an embodiment of the present invention, and FIG. 2 is also used as an explanatory diagram of fuzzy inference processing of the embodiment. The noise characteristics of the third test are as described above.

In one embodiment of the invention to be described next, the receiver has F
Assume that it is an M stereo receiver. Further, it is assumed that the input vector has two elements, the received electric field strength value E and the detected noise level value N, and the fuzzy production rules are two rules, R1 and R2.

(A) Configuration of Embodiment In FIG. 4, the noise reduction means 11, input level detection circuit 12, output noise level detection circuit 13, fuzzy inference means 4 and fuzzy control signal ordering circuit 15 are explained in FIG. As I said.

16 is an FM demodulation circuit, which demodulates a composite signal of FM stereo signals.

Reference numeral 17 denotes an MPX demodulation circuit, which demodulates left and right stereo signals and R from a composite signal subjected to noise reduction processing.

In this embodiment, the noise reduction means 11 includes a stereo noise control circuit (hereinafter referred to as an SNC circuit) 111 and a high cant control circuit (hereinafter referred to as an HCC circuit) 112.

The SNC circuit 111 performs processing to control the level of the sub-signal component in the composite signal demodulated by the FM demodulation circuit 16.

The HCC circuit 112 extracts the main signal (L+R) component from the composite signal demodulated by the FM demodulation circuit i16, and performs processing to control its high frequency characteristics.

The input level detection circuit 12 outputs a received field strength value E obtained by detecting the IF multiplied signal AM of the FM demodulation circuit 16 as a received input level.

In the output noise level detection circuit 13, 131 is a high-pass filter, which extracts high-frequency components (for example, 20 kHz or more) included in the left and right stereo signals output from the MPX demodulation circuit 17 as noise components.

A level detector 132 performs AM detection on the noise component from the high-pass filter 131 and outputs it as a detected noise level value N.

The fuzzy control signal generation circuit 15 uses the fuzzy inference means 1
The final inference result of step 4 is set as the reference voltage Vs, and this reference voltage V
SNC control signal and HCC control signal which are fuzzy control signals are generated from the difference signal between s and noise level detection value N, and are supplied to SNC circuit 111 and HCC circuit 112, respectively.

(B) Fuzzy inference processing The fuzzy inference means 14 uses the received electric field strength value detected by the input level detection circuit 12 and the output noise level detection circuit 13
Fuzzy inference processing is performed using the detected noise level detection value as a hydraulic condition.The fuzzy inference processing of this embodiment performed by the fuzzy inference means 14 will be explained with reference to FIG.

In the fuzzy inference processing of this embodiment, the following two fuzzy production rules R1 and R2 and membership functions giving each fuzzy production rule are set.

These fuzzy production rules and membership functions are set theoretically or experimentally so that a good reception condition can be obtained corresponding to the received electric field strength value E and the detected noise level value N.

(1) Fuzzy production rule R1 ■ Preconditions (
IF): a,: Received electric field level is high.

bI: Low noise level.

■Result (consequent part, THEN): Reduce the level of the reference voltage Vs, which is the final inference result.

(2) Each membership function of fuzzy production rule R1: ■Membership function mA+ of premise a, 2nd
Figure (a) shows the prerequisite a, that is, the membership function mAz that gives the likelihood of the received electric field level.

In the membership function mA, the horizontal axis indicates the received electric field strength E, and the joint axis indicates the degree to which the precondition a1 is satisfied. Prerequisite a.

The degree value is 1 when it is completely true, and the degree value is O when the precondition a is not completely true.
It is. The figure shows that as the received signal strength E increases,
This shows that the degree to which precondition a1 is applied increases.

■Membership function mB of precondition b1: Figure 2 0
)) represents a prerequisite, that is, a membership function mB that gives the smallness of the detected noise level value N.

In the membership function mB, the horizontal axis indicates the noise level detection value N, and the vertical axis indicates the degree to which the precondition . The degree value is 1 when the prerequisite (i) is completely met, and the degree value is 0 when the prerequisite (i) is not completely met. The figure shows that as the detected noise level value N becomes larger, the degree to which the prerequisite condition (i) is satisfied becomes smaller.

■ Membership knob function mP that gives the result.

FIG. 2(C) shows the inference result, that is, the membership function mP that provides the reference voltage Vs.

In the membership function mP, the horizontal axis is the reference voltage V
s, and the vertical axis indicates the degree to which the results apply. The degree value is 1 when the result is completely applicable, and the degree value is 0 when the result is not completely applicable.

The figure shows that as the reference voltage Vs becomes larger, the degree to which the results apply becomes smaller.

(3) Fuzzy production rule R2 ■ Preconditions (
IF): az: Received electric field level is low.

b2: The noise level is high.

■Result (Consequent part, THEN): The level of the reference voltage Vs, which is the final inference result, is increased.

(4) Each membership function of fuzzy production rule R2: ■ Membership function mA2 of precondition a2: Figure 2 (d) shows the membership function mA that gives precondition a2, that is, the smallness of the received electric field level. It is something that

The content of the membership function mAz is the same as the membership function mA, or, contrary to the membership function mA, as the received electric field strength E increases, the degree to which the precondition a2 is satisfied decreases. It shows.

■Membership function mB of precondition b2: Figure 2 (
e) shows the prerequisite b2, that is, the membership function mBz that gives the likelihood of the noise level detection value N being large.

The content of the membership function mBz is the same as the membership function mB, or contrary to the membership function mB, as the noise level detection value N increases,
This shows that the degree to which precondition b2 is applied increases.

■The membership function mP that gives the result (Figure 4) shows the inference result, that is, the membership function mP that gives the reference voltage ■S.

The content of the membership function mPz is the same as the membership function mP, but contrary to the membership function mP, it shows that as the reference voltage ■S increases, the degree to which it applies to the result increases. ing.

(5) Fuzzy inference processing The fuzzy inference processing performed by the fuzzy inference means 14 is
The explanation will be given according to the inference procedure.

■ The values of the membership functions mA and mAz for the received electric field strength value E in the input conditions are determined, and the values are shown in Fig. 2 (a
) and (d), respectively.

and u2 values are obtained.

(2) The values of the membership functions mB and mBz for the noise level detection value N in the input conditions are determined, and the values of V and v2 are obtained from FIGS. 2(b) and (e), respectively.

■ First, inference processing is performed using the fuzzy production rule R1.

Observed received electric field strength value E and noise level detection (i
There are various methods for determining the degree to which the membership functions mA and mB match the fuzzy production rule R1 (soft matching) from the values of each membership function corresponding to N, but in this example, is calculated by the minimum method.

In the minimum method, the minimum value of the degree values that match each observed value of the input condition of each membership function giving the fuzzy production rule is selected as the value of the degree that matches the fuzzy production rule R1 of each membership function.

Membership function mA corresponding to each observed value of the input condition, that is, the received electric field strength value E and the detected noise level value N
, and mB, the magnitude relationship between the values U and Vll is, u, >
v, so by the minimum method the membership function mA
■ is selected as the value of the degree to which 1 and mB match the fuzzy production rule R1.

Since the value of the degree of matching with the fuzzy production rule R1 is vl, the fuzzy production rule R
Membership function mP+ that gives the inference result by 1
is represented by a region lower than vl, as indicated by diagonal lines in FIG. 2(C), by the 'lager head-cutting method.

(2) Next, inference processing using the fuzzy production rule R2 machine is performed.

As in the case of the fuzzy production rule R1, the magnitude relationship between the values u2 and v2 of the membership functions mAz and mB corresponding to the observed received electric field strength E and noise level detection value N is u2<v2. By the minimum method, the degree to which the membership functions mAz and mBz match the fuzzy production rule R2 is:
u2 will be selected.

Since the value of the degree of matching with the fuzzy production rule R2 is u2, the fuzzy production rule R
The membership function mHz that gives the inference result based on U2 is expressed by Yager's truncated method in a region lower than u2, as shown by diagonal lines in FIG. 2(f).

(2) There are various methods for determining the final inference result based on the results of (1) and (2) determined by the fuzzy production rules R1 and R2, but in this embodiment, the centroid method is used.

In the centroid method, first, each membership function mP and mP2 (hatched area) shown in Fig. 2 (C) and (f) are superimposed using the MAX synthesis method, and then synthesized as shown in Fig. 2 (8). A membership function mPo is synthesized.

Then, this composite membership function mP. The horizontal axis coordinate value of the center of gravity is output as the final inference result F, that is, the reference voltage Vs.

Through the above inference processing, the larger the received electric field strength value E and the smaller the noise level detection value N, that is, the better the reception condition, the smaller the reference voltage VsO value, which is the final inference result. The smaller the intensity value E and the larger the noise level detection value N, that is, the worse the reception condition, the larger the reference voltage VsO value, which is the final inference result.

(C) Noise reduction operation The fuzzy control signal generation circuit 15 uses the fuzzy inference means 1
The final inference result of step 4 is set as the reference voltage Vs, and this reference voltage V
The SNC control signal and the HCC control signal, which are fuzzy control signals, are generated from the difference signal between s and the noise level detection value N, and are supplied to the SNC circuit 111 and the HCC circuit 112, respectively.

The control operation start voltage of the SNC circuit 111 is the same as that of the HCC circuit 1.
It is set lower than the control operation start voltage of No. 12. Therefore, when the level of the received electric field strength value E decreases and the levels of the SNC control signal and HCC control signal generated by the fuzzy control signal generation circuit 150 increase, first the SNC circuit 1
11 works.

The SNC circuit 111 lowers the level of the sub-signal part in the composite signal input from the FM demodulation circuit 16 as the level of the HCC control signal increases, that is, as the received field strength value E decreases and the noise level increases. let

As a result, as the received electric field strength (1iE) decreases and the noise level increases, the separation of the left and right stereo signals output from the MPX demodulation circuit 17 (R) decreases, or the separation of the left and right stereo signals (R) increases. This will reduce the noise level.

The level of the received electric field strength value E further decreases, and the fuzzy control signal generating circuit 150 generates SNC! I1m signal and H
When the level of the CC control signal increases further, the HCC circuit 112 also starts operating.

The HCC circuit 112 extracts the main signal (L+R) component from the composite signal input from the FM demodulation circuit 16 and performs processing to control its frequency characteristics. That is, as the received electric field strength value E decreases and the noise level increases, and the level of the HCC control signal increases, the main signal (L
+R).

As a result, as the received electric field strength value E decreases and the noise level increases, the separation and high frequency characteristics of the left and right stereo signals output from the MPX demodulation circuit 17 decrease, or the left and right stereo signals Therefore, the noise level contained in R can be reduced.

Although one embodiment of the present invention has been described above, the present invention is not limited to this embodiment.

For example, the noise reduction means 11 may be provided after the MPX demodulation circuit 17. Furthermore, the noise reduction circuit may also include a muting control circuit.

Furthermore, the characteristics of each fuzzy production rule and each membership function that provides each of these rules can use various characteristics and rules other than those shown in FIG. 2.

In addition to the centroid method explained in the embodiment, as a method for obtaining the final inference result, that is, the motion sensitivity point SE, based on the inference result by each membership function that provides the antecedent part of each fuzzy production rule, the MAX- Various known zero methods such as the MIN method can be used.

〔Effect of the invention〕

As explained above, according to the present invention, the following effects can be obtained.

(1) Since the noise reduction operation of the noise reduction circuit in the receiver is fuzzy controlled, it is possible to increase the noise control range and perform good noise reduction in a wide reception input range.

(2) It is possible to both improve the noise reduction effect and reproduce audio signals of good quality.

[Brief explanation of drawings]

Fig. 1 is an explanatory diagram of the basic configuration of the present invention, Fig. 2 is an explanatory diagram of the fuzzy inference processing of the present invention and the embodiment, Fig. 3 is an explanatory diagram of the noise control characteristics of the present invention, and Fig. 4 is an explanatory diagram of the present invention. FIG. 5 is an explanatory diagram of a conventional noise reduction circuit, and FIG. 6 is an explanatory diagram of noise control characteristics of the conventional noise reduction circuit. 1 and 4, 10... noise reduction circuit, 11... noise reduction means, I2... input level detection circuit, 13... output noise level detection circuit, 14... fuzzy inference means, 15
. . . Fuzzy control signal generation circuit, 16 . . . FM demodulation circuit, 17 . . . MPX demodulation circuit.

Claims (1)

[Scope of Claims] A noise reduction circuit (10) that performs processing to reduce various types of noise contained in a received input includes: (a) noise reduction means (11) that performs control to reduce noise components in the received input; (b) an input level detection circuit (12) that detects the received field strength value of the received input; (c) an output noise level that detects the noise level included in the output signal after noise reduction processing by the noise reduction means (11); The detection circuit (13) and (d) the received electric field strength value detected by the input level detection circuit (12) and the noise level detection value detected by the output noise level detection circuit (13) are used as input conditions, and for each of the above detection values. Fuzzy inference means (14) that performs fuzzy inference according to the fuzzy production rule given by the membership function of 1. A noise reduction circuit comprising: a fuzzy control signal generation circuit (15) for controlling the noise reduction operation performed by the noise reduction means (11) based on the noise reduction means (11).