JP2000268502A - Information reproducing device using feedback filter - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve the error rate by selecting a data stream corresponding to a path providing a minimum path metric on the basis of a state transition diagram introduced from an output of an impulse response waveform and a depth of a tree so as to obtain a compensation value for equalization. SOLUTION: A metric computing device 2 outputs an equivalent error E, a path metric L of a survival path and a survival path P corresponding to each state on the basis of a state transition diagram. A comparator 3 outputs a path state numbers providing a minimum value to the path metric L and an equivalent error εi corresponding to a most probable path. A selector 5 uses the state number S to select one of a plurality of data streams D corresponding to the survival path P stored in a path memory 4 and to output a tentatively detected data stream d*. A feedback filter 6 obtains and outputs a compensation value to equalize a trailing edge of an impulse response of an output of a feedforward filter 1 to '0' on the basis of the tentatively detected data stream d*.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an information reproducing apparatus for reproducing digital information recorded on a magnetic disk, a magnetic tape, an optical disk or the like, and more particularly to an information reproducing apparatus having a feature in data detection.

[0002]

2. Description of the Related Art In a digital recording / reproducing apparatus such as a magnetic disk device and an optical disk, a recording data reproducing method is
P combining partial response method and maximum likelihood detection method
The RML (Partial Response Maximum Likelihood) method is used. Furthermore, in order to cope with the recent increase in recording density, in magnetic recording, a method has been proposed in which a modulation method capable of increasing the minimum inter-code distance is combined with the EEPR4 method, which is a higher-order PRML method (Jaekyun Moo).
n and Barrett Brickner, "Maximum TransitionRun Cod
es for Data Storage Systems ", IEEE Transactions on
Magnetics, vol. 32, no. 5, Sept. 1996).

In addition to the PRML method, a RAM-DFE (Dec) is used as a detector using a feedback filter.
ision Feedback Equalizer), FDTS / DF (Fi
xedDelay Tree Search / Decision Feedback) method is also being studied.

In the FDTS / DF method, a path length is limited, and a path having the smallest path metric is selected with the limited path length in contrast to the maximum likelihood detection method in which the time until data is identified is indefinite. This is intended to cope with the above-mentioned increase in recording density.

FIG. 11 is a block diagram showing the configuration of an apparatus using the FDTS / DF method.

The reproduced waveform is a feedforward filter 1
After passing through 101, it is set to ai (i is a time), then to yi via an adder and input to the FDTS detector 1111. Although FDTS detector 1111 output d _{i-gamma +1} is the detected data are input to the delay element 1107 ₁ simultaneously. A plurality of delay elements are provided.
_{7 1, 1107 2, ...,} 1107 n is connected to a serial, each n delay element output d _i- γ, d _i- γ
₋₁ ,..., D _i− γ _{−n + 1} are output to the feedback filter (FB) 6 as a data string D corresponding to each state from i−γ to i−γ + n−1 with respect to the current time i. Have been.

The output bi of the feedback filter 1106 is input to the adder described above, and added to the output ai of the feedforward filter 1101 to obtain yi.

In this conventional example, the FDTS detector 1111 obtains and outputs detection data delayed by γ-1 (γ is the depth of the tree).

FIG. 12 and FIG.
FIG. 3 is a diagram illustrating a determination method of S and an impulse response.

The impulse response is a response to the recording data "1". In magnetic recording, a reproduced waveform corresponds to a dipulse, which is two continuous solitary waves having inverted polarities. FIG. 12 and FIG. 13 are examples of the tree depth γ = 2. As shown in FIG. 12, at time i, branch metrics and path metrics for four paths (trees) are obtained and compared to determine a path that gives the smallest path metric. And i-γ in that path
The data at the point of time +1 is output as determined determination data.

The detected data string before the time point i-γ + 1 obtained as described above is fed back to the feedback filter 110.
As an input value to 6, waveform compensation at the next (i + 1) time point is performed.

FIG. 13 is an example of an impulse response waveform. The output value at the discrimination point is set to “1” by the feedforward filter 1101, and the output value before that is equalized to “0”. After the point delayed by γ bits from the discrimination point, it is equalized to “0” by the feedback filter 1106. As a result, the equalized waveform becomes the output value (1 and a) of the remaining γ bits (here, 2 bits).
And metric calculation and data detection are performed according to the determination method shown in FIG.

[0013]

According to the FDTS / DF method, the FDTS method is used for data detection. In this method, the path length is limited, and a path metric is obtained for a limited number of paths. Therefore, there is a possibility that the error rate characteristics are worse than the maximum likelihood detection method.

When the maximum likelihood detection method is used, the time until data is identified is indefinite, and the detected data cannot be obtained within a limited delay. The feedback loop cannot be operated within (clock).

SUMMARY OF THE INVENTION The present invention has been made in view of the above-mentioned problems of the prior art, and uses a maximum likelihood detection method and can operate a feedback loop with a predetermined delay amount. An object of the present invention is to realize an information reproducing apparatus using a highly accurate feedback filter with an improved rate.

[0016]

An information reproducing apparatus using a feedback filter according to the present invention equalizes the leading edge of an impulse response of a reproduced waveform, sets an output value at a discrimination point to "1", and A feed-forward filter that sets the previous output value to “0”, a feedback filter that compensates for the trailing edge after the point of tree depth γ bits behind the identification point, the feed-forward filter output and the feedback filter output, Are equalized errors E for each equalization reference level value, a branch metric for each branch, and a path metric based on a tree transition γ and a state transition diagram derived from a waveform output of an impulse response from the superimposed waveform. And compare the path metric to each state, and generate the path with the minimum path metric to that state. A metric calculator to be selected as a surviving path and a surviving path selected by the metric calculator are input.
A path memory in which n data up to the point of −γ + n−1 output a data string D corresponding to each state and a value of a final stage as detection data, and a surviving path to each state obtained by the metric calculator. And a data string D output from the path memory, and a data string corresponding to the path giving the minimum path metric obtained by the comparator is input. A selector for selecting and outputting to the feedback filter, wherein the feedback filter obtains a compensation amount for equalization based on the data sequence selected by the selector.

In this case, the path memory length may be shorter than the number of input data of the feedback filter, and a delay element for holding the detection data output from the path memory and outputting the detected data to the feedback filter may be provided.

In any of the above cases, the selector selects the equalization error corresponding to the path having the minimum path metric from the equalization errors corresponding to each surviving path, and determines the selected equalization error. The adaptive equalization of the feedforward filter and the feedback filter may be performed by using this.

The feedback filter and the metric calculator have a tree depth γ of 2, and the metric calculator has a state transition diagram of two states with respect to the reproduced waveform on which the output of the feedforward filter and the output of the feedback filter are superimposed. May be performed to perform maximum likelihood detection.

The feedback filter and the metric calculator have a tree depth γ of 3, and the metric calculator has four state transitions with respect to the reproduced waveform on which the output of the feedforward filter and the output of the feedback filter are superimposed. Maximum likelihood detection may be performed in correspondence with the diagrams.

Further, the feedback filter and the metric calculator have a tree depth γ of 4, and the metric calculator has eight state transitions with respect to the reproduced waveform on which the output of the feedforward filter and the output of the feedback filter are superimposed. Maximum likelihood detection may be performed in correspondence with the diagrams.

In the information reproducing method using the feedback filter of the present invention, the leading edge of the impulse response of the reproduced waveform is equalized, the output value at the discrimination point is set to "1", and the output value before that is set to "1". 0 "and a first step of compensating for the trailing edge after the point of delay of the tree depth γ bits from the discrimination point to obtain an equalized waveform. From the equalized waveform, the tree depth γ and the impulse response An equalization error E for each equalization reference level value, a branch metric for each branch, and
A second step of obtaining a path metric, comparing path metrics to each state, and selecting a path having the smallest path metric as a surviving path to the state, and a surviving path selected in the second step On the basis of the,
A third step of generating n data strings D corresponding to the respective states from i−γ to i−γ + n−1 with respect to the current time i and in which data at the last stage is detected data; A fourth step of obtaining a path having a minimum path metric from the surviving paths to each state obtained in the second step, and n generated in the third step.
A fifth step of selecting a data string corresponding to a path giving the minimum path metric obtained in the fourth step based on the data strings D, and a fifth step of selecting a data string selected by the selector. And calculating a compensation amount for equalization performed in the first step.

[Operation] In the FDTS detector, the path metric calculation is terminated up to the tree depth γ, and the minimum path metric is obtained. In the present invention, the maximum likelihood detection is performed similarly to the PRML method.

In the present invention, first, a branch metric and a path metric are calculated by a metric calculator based on a state transition diagram obtained from a γ value and an impulse response, and a surviving path for each state is determined. However, the judgment standard level is a general PRM
Unlike the L method, it is not an integer value but a real value, and can be arbitrarily given. Path memory is a general PR
It has the same configuration as that of the ML system, and can perform maximum likelihood detection.

A feedforward filter and a feedback filter are used to perform waveform equalization. FD
Similar to the TS / DF method, the leading edge of the impulse response is equalized by the feedforward filter, and the output value at the discrimination point is set to “1” and the output value before that is set to “0”. On the other hand, the feedback filter compensates for the trailing edge after the point of γ bits delay from the discrimination point.

The above-described waveform equalizing operation is the same as the FDTS / DF method. As the input value to the feedback filter in the present invention, a detection value corresponding to the most probable path at the present time from a plurality of detection data strings recorded in the path memory is used as the temporary detection data string instead of the FDTS detection result. This tentative detection data string is a detection data string corresponding to the path when the path metric of the surviving path corresponding to each state is compared to find the path giving the minimum path metric.

To summarize the above operation, the state transition diagram which is the basis of the maximum likelihood detection is determined by the metric calculator from the γ value and the impulse response waveform and recorded in the path memory. The comparator finds the minimum value of the path metric corresponding to a plurality of surviving paths recorded in the path memory. The selector selects, from the data string D in the path memory, the most likely data string at the present time (the data string corresponding to the path with the smallest path metric) as the temporary detection data from the data string D in the path memory based on the minimum value of the path metric obtained by the comparator. The selected tentative detection data is input to the feedback filter. Using the feedback filter and the feedforward filter, the leading edge and the trailing edge of the impulse response are compensated.

As described above, in the present invention, the FDT
Since the maximum likelihood detection method (Viterbi detection method) is used instead of the FDTS detection method used in the S / DF method, the error rate is improved. In addition, by using the most probable data sequence at the present time from the data sequence recorded in the path memory as the tentative detection data, it is possible to perform a feedback operation with a predetermined delay amount, and it is a highly accurate detector. .

[0029]

Next, an embodiment of the present invention will be described with reference to the drawings.

FIG. 1 is a block diagram showing a main configuration of an information reproducing apparatus using a feedback filter according to the present invention, and shows a configuration of a portion for generating detection data from a reproduced waveform obtained from a reproducing head which is a detector. Is shown.

This embodiment uses a metric calculator (ACS) 2 and a path memory 4 used in a PRML system or the like in place of the FDTS detector in the data detector of the FDTS / DF system. It comprises a feedforward filter (FF) 1, a comparator 3, a selector and a feedback filter 6 provided separately.

The reproduced waveform obtained from the reproducing head (not shown) is equalized to “0” at the leading edge from the discrimination point of the impulse response waveform by the feedforward filter (FF) 1 and becomes “1” at the discrimination point. ”(I is time). The output ai of the feedforward filter 1 is a feedback filter (FB)
6 is added to the output bi, and is output as yi to the metric calculator (ACS circuit) 2. The output ai of the feed-forward filter 1 is added to the output bi of the feedback filter 6 so that the trailing edge of the bit number (tree depth γ) determined from the rising position is equalized to “0”. Becomes The definition of the tree depth γ is the same as the definition in the FDTS / DF method, and indicates the number of bits from the discrimination point to the position where the feedback filter 6 equalizes.

In the metric calculator 2, based on the state transition diagram derived from the tree depth γ and the impulse response waveform output, the input yi (equalized waveform) is used to calculate an equalization error E, A branch metric and a path metric for each branch are obtained. Then, the path metrics to each state are compared, and the path with the smallest path metric is selected as the surviving path to that state.

The metric calculator 2 performs the above operation.
The equalization error E and the path metric L of the surviving path corresponding to each state are output to the comparator 3, and the surviving path P (selection result) is output to the path memory 4.

The comparator 3 obtains the minimum value of the path metric L of the surviving path to each state, outputs the state number S corresponding to the path giving the minimum value to the selector 5, and at the same time, equalizes the state number S with the state number S. From the error E, an equalization error εi corresponding to the most probable path is selected and output to the feedback filter 6.

The selector 5 selects one of the plurality of data strings D corresponding to the surviving paths recorded in the path memory using the selected state number S, and selects the temporarily detected data string d.
Output ^* . The provisional determination data sequence d ^* is a data sequence before the time point delayed by γ bits from the current time i. In the FB, based on this d ^* , the trailing edge of the impulse response of the FF output (delayed by γ bits from the rising edge) A compensation value for equalizing (before the time point) to “0” is obtained and output. On the other hand, as the final detection data d, the final stage output of the path memory is used without using the temporary detection data.

Next, the operation of this embodiment will be described.

First, the operation principle of the feedforward filter 1 and the feedback filter 6 in FIG. 1 will be described. FIG. 2 shows impulse response waveforms corresponding to some γ values. Here, assuming a magnetic recording device,
"1" of the recording data is made to correspond to a dipulse (a continuous waveform of two isolated waves having different polarities) in the reproduction waveform. That is, (1-D) conversion is performed on the recording data, and the isolated wave is made to correspond to the point where the conversion data becomes "± 1". γ is defined similarly to the tree depth in FDTS / DF, and γ bits from the discrimination point are used for maximum likelihood detection without being equalized by the feedback filter 6.

FIG. 2A shows γ = 2, and FIG. 2B shows γ = 2.
3. Fig. 2 (c) shows an equalized waveform with γ = 4 (impulse response)
This is an example.

In each impulse response waveform,
The leading edge is equalized by the feedforward filter (FF) 1 from the point of time when it first goes from 0 to +1 (identification point), and all are equalized to “0”.

The waveform output values a, b, and c after the discrimination point shown in FIG. 2 are arbitrary values, and may be determined in consideration of the characteristics of the reproduced waveform, the error rate, and the like.
If the reproduced waveform does not change, the value of c is determined by the feedforward filter 1, so it can be considered that the value of c is equalized by the feedforward filter 1.

On the other hand, the equalization of the trailing edge from the discrimination point to the time after γ is performed by the feedback filter (FB) 6, and all are equalized to “0”. Since the feedback filter 6 performs compensation based on the determination result at the discrimination point, it is not affected by noise unless a determination error occurs. As described above, an impulse response waveform is obtained in which all bits except for the γ bits from the identification point are equalized to “0”.

The equalized waveform y obtained as described above is
It is input to a metric calculator (ACS circuit) 2 of the maximum likelihood (Viterbi) detector shown in FIG.

FIG. 3 shows a basic state transition diagram for performing metric calculation for maximum likelihood detection in the present embodiment. 3A shows an example in which γ = 2, FIG. 3B shows an example in which γ = 3, and FIG. 3C shows an example in which γ = 4. These state transition diagrams are configured based on the impulse response waveforms shown in FIG. 2, and the values shown in each branch represent detection data and an equalization reference value. Based on such a state transition diagram,
A branch metric and a path metric are obtained from a difference from the equalization reference value (equalization error E), and a surviving path for each state is determined. In the conventional ACS circuit, only the surviving path P is output to the path memory, but the metric calculator (ACS circuit) in the present embodiment is used.
2, the path metric L and the equalization error E for each surviving path are also output at the same time.

The output path metric L and the equalization error E
Is input to the comparator 3 shown in FIG. The comparator 3 compares the path metric L corresponding to each state,
The state number S corresponding to the path giving the minimum path metric value is obtained. Further, a corresponding value is selected from the equalization error E based on the state number S, and is output as the equalization error εi. When the feedforward filter (FF) 1 and the feedback filter (FB) 6 are filters with fixed parameters, the equalization error εi is not necessary, but when performing adaptive equalization, the equalization error εi is used. Adaptive equalization is performed on the parameters of the feedforward filter (FF) 1 and the feedback filter (FB) 6, and the parameters can be sequentially changed. In the adaptive equalization of the feedforward filter (FF) 1, the parameter is changed so that the leading edge of the impulse response is "0" and the waveform output value of the γ bits from the identification point matches the value shown in FIG. That is, the feedback filter (F
B) The adaptive equalization of 6 sets the trailing edge of the impulse response to "0".
Is to change the parameter so that

The structure of the path memory 4 is basically the same as that of the conventional PRML system. The changes are that the values at the first stage are changed based on the state transition diagram, and that the contents of the path memory 4 are data strings D corresponding to each state, i-γ to i- γ + n
−1 until the time point −1, the feedback filter (F
B) It is output as an input candidate to 6.
The change of the initial stage value of the path memory 4 makes the initial stage selector meaningless, so that the initial stage delay element and the selector can be deleted.

In the selector 5, from these data strings D
The most probable tentative judgment data at the moment according to the state number S
Row d^*Is selected. Feedback filter (F
B) 6 is the data string d^*Waveform equalization based on
Is output. On the other hand, in the present embodiment,
The detection data d as a detector is the above-mentioned provisional detection data d
^*Instead, they are output from the last stage of the path memory.
Therefore, take a long enough path memory and converge the path.
The result of the maximum likelihood determination is obtained.

In this embodiment, the γ value can be set to two or more values. Also, the waveform output values after the discrimination point of the impulse response can be set in advance and maintained by performing adaptive equalization on the feedforward filter (FF) 1. A state transition diagram for maximum likelihood detection may be created based on these values.

Next, the operation of the above-described embodiment will be described more specifically by taking the case where the tree depth γ = 3 as an example.

FIG. 4 is a diagram showing an equalization process of a reproduced waveform corresponding to the recording data "1" (an impulse response equalization process). The equalization process will be described in detail with reference to FIG.

The solid waveform is the impulse response of the feedforward filter (FF) 1. The point (identification point) at which the output value rises by the feedforward filter (FF) 1 is set to “1”, and the leading edge is equalized to 0 from that point. At this time, equalization is not performed on the trailing edge of the identification point. Since the feedback filter (FB) 6 in the present embodiment outputs the compensation value with a delay of γ bits, the feedback filter (FB) 6 can compensate from the point of time γ bits behind the discrimination point. The arrows at each time point indicate the amount of compensation, and the dotted line shows the equalized waveform after compensation by the feedback filter (FB) 6. The values of a and b are arbitrary, and are determined by the characteristics of the reproduced waveform. The form of the feedforward filter (FF) 1 and the form of the feedback filter (FB) 6 are also arbitrary.

Feed forward filter (FF) 1
Since it is sufficient if the reproduced waveform can be equalized as shown by the solid line in FIG. 4, an analog filter, a transversal filter, or the like can be used. Feedback filter (FB) 6
Since it is sufficient that a compensation value for equalization can be output from the detection data string, a transversal filter or a RAM table can be used.

The metric calculation may be performed based on the state transition diagram shown in FIG. 3B, and is basically the same as the conventional ACS circuit. The difference is that, in addition to the surviving path P _0-3 corresponding to each state, the path metric value L _0-3 and the equalization difference E _0-3 corresponding to the four surviving paths are output.

FIG. 5 shows the structure of the comparator 3 for obtaining the smallest path metric from these path metrics L _0-3 and obtaining the corresponding state number S and the equalization error ε for adaptive equalization. The comparator 3 includes a comparator 10 and a selector (S) 9. The comparator 10 compares the four path metrics L _0-3 and outputs a state number S that gives the minimum value. The selector (S) 9 outputs Es as an equalization error εi from four input values (equalization errors E _0-3 ) based on the state number S.

FIG. 6 shows the path memory 4 and the selector 5
Is shown. The configuration of the path memory is basically the same as that of the conventional PRML system. However, the state transition diagram 3 (b)
, The first-stage selector selects from the same value, so that the first-stage delay element and the selector are omitted. Also, an n-stage data string D is output to the outside in accordance with n bits of input data of the feedback filter (FB) 6. The data D from each stage (at each time point) is four pieces of data corresponding to the state, and is the determination data corresponding to the surviving path of each state.

The selector 5 selects the data at each point in time according to the state number S, and outputs the most probable tentative judgment data string d ^* at the present time. The final detection data is output from the rear end of the path memory 4. At this time, the path memory length is determined by the feedback filter (FB).
6 may be used when the number of input data is longer than the number of input data. However, when the number of input data is short, the detection data may be held using a delay element and input to the feedback filter (FB) 6. Such a configuration may be adopted.

FIG. 7 illustrates the process of determining the tentative judgment data sequence.
FIG. 7A is a diagram for clarifying a trellis diagram.
It is an example. The surviving path at the point i is indicated by a solid line.
You. When such a survival path is required,
In the memory, data as shown in FIG. 7B is recorded.
Have been. When the surviving paths merge,
The judgment data all match. Here, i-3
And the detection data before that has not been determined.
You. Path metric L of surviving path at present _0-3of
Among them, L is the minimum value.₁If
The enclosed data string corresponding to the state S1 is selected, and the
Used as an input to the feedback filter (FB) 6.
You.

As described above, feedback can be applied with a delay of the γ clock as in the FDTS / DF system. FIG. 8 shows an equalization reference value and a branch metric for performing metric calculation. The branch metric and the path metric are calculated based on these equations, and the maximum likelihood detection is performed. The amount of calculation can be reduced by calculating the equalization reference value R and a constant derived from R in advance.

Next, a second embodiment of the present invention will be described with reference to FIG.
This will be described with reference to FIG.

This embodiment is different from the first embodiment in that the comparator 3, the path memory 4 and the selector 5 are replaced with a comparator 903, a path memory 904 and a selector 905, respectively. FIG. 10 is a diagram illustrating a configuration of a comparator 903 according to the second embodiment of the present invention.
FIG. 9 is a diagram showing a configuration of a path memory 904 and a selector 905 according to a second embodiment of the present invention. The other configurations are the same as those of the first embodiment, and thus only these configurations will be described.

In the embodiment shown in FIGS. 5 and 6, the number of clocks required for a signal to propagate through the feedback loop is only one clock. With this one clock,
It is necessary to calculate an equalization waveform, calculate a branch metric and a path metric, select a surviving path, detect a minimum path metric, select provisionally detected data, and calculate a compensation amount using a feedback filter 6 (FB). ,
Very heavy circuit load. Thus, in the second embodiment, it is possible to increase the number of clocks required for transmitting a signal through the feedback loop.

FIG. 9 shows the configuration and operation of this embodiment.
With reference to FIG. 10 and FIG. In the comparator 903 of this embodiment, the delay element (D) 907 ₁ ,
907 ₂ is provided, and the path memory 904 is provided with a delay element (D) 907 ₃ . Each of these delay elements (D) delays the path metric L, the equalization error E, and the selected branch (surviving path) P output from the ACS circuit 2 by one bit. Instead, the path memory 904
Is shifted by one bit from the data sequence D output from
Output at an earlier point in time). As described above, the operation of the feedback loop can be performed with a margin of one clock in time. However, in this method, the accuracy of the provisional determination data d ^* is reduced because the output from the stage number lower by one bit in the path memory is used.

In order to obtain a time margin of k bits (clock), the output position of the data D shown in FIG. 10 is shifted toward the lower stage number of the path memory, and a delay element is inserted somewhere instead. Good. At this time, the timings of the respective calculations are not shifted. Thus, the feedback loop operates with 1 + k clocks.
In addition, since the equalization error for performing the adaptive equalization may deviate from the time point i, the adaptive equalization is also performed accordingly. In this method, the feedback loop can generally be operated with a delay of at most γ-1 bits.

[0064]

Since the present invention is configured as described above, the following effects can be obtained.

In the FDTS / DF method, the error rate can be improved by using the maximum likelihood detection method (Viterbi detection method) used in the PRML system instead of the FDTS detection.

[Brief description of the drawings]

FIG. 1 is a block diagram showing the overall configuration of a detector according to the present invention.

FIG. 2 is a diagram showing an impulse response to each γ in the present invention.

FIG. 3 is a state transition diagram for each γ in the present invention.

FIG. 4 is a diagram showing a waveform equalization method for γ = 3 in the present invention.

FIG. 5 is a diagram showing a detailed configuration when γ = 3 in the comparator 3 of FIG. 1;

6 is a diagram showing a detailed configuration when γ = 3 in the path memory 4 and the selector 5 in FIG. 1;

FIG. 7 is a diagram showing an example of the operation of the path memory 4 and the selector 5 of FIG. 6;

FIG. 8 is a diagram showing a metric calculation formula when γ = 3 in the ACS circuit 2 of FIG. 1;

FIG. 9 is a diagram showing a configuration of a comparator 3 when γ = 3 in another configuration of the present invention.

FIG. 10 is a diagram showing a configuration of a path memory 4 and a selector 5 when γ = 3 in another configuration of the present invention.

FIG. 11 is a block diagram showing a configuration of an FDTS / DF method as a conventional example.

FIG. 12 shows a tree search (FDTS) detection method of the FDTS / DF method as a conventional example.

FIG. 13 is a diagram showing an impulse response waveform of the FDTS / DF method as a conventional example.

[Explanation of symbols]

REFERENCE SIGNS LIST 1 FF (feedforward filter) 2 ACS circuit (metric calculator) 3 comparator 4 path memory 5 selector 6 FB (feedback filter) 7 1-bit delay element 8 selector (2 inputs, 1 output) 9 selector (4 inputs, 1 Output) 10 Comparator (minimum path metric detector) 11 FDTS detector ai FF output yi Equalized waveform bi FB output P Surviving path for each state L Path metric for each surviving path E Equalization error for each surviving path D Each surviving Detected data sequence for path d ^* Temporary detected data sequence (corresponding to the path with the smallest path metric among surviving paths) d Detected data sequence (output of last stage of path memory) γ tree depth (Definition is based on FDTS / DF N) Number of input data of n FB m Path memory length εi Equalization error (temporary S Selection state number (corresponding to the path having the smallest path metric among surviving paths) i Time a, b, c Impulse response waveform output value R Equalization reference value B Branch metric

Claims (6)

[Claims] 1. A feedforward filter for equalizing a leading edge of an impulse response of a reproduced waveform, setting an output value at an identification point to “1” and an output value before that to “0”; A feedback filter for compensating for the trailing edge after the point of delay of the tree depth γ bits from the point, and an equalized waveform in which the feedforward filter output and the feedback filter output are superimposed, the tree depth γ and the impulse response The equalization error E for each equalization reference level value, the branch metric for each branch, and the path metric are obtained based on the state transition diagram derived from the waveform output, and the path metric for each state is compared. A metric calculator that selects a path to be a surviving path to the state; and Enter the-option has been survivor path for current i, from i-γ i-γ + n-1
The data string D corresponding to each state is n data up to the time point.
And a path memory that outputs a value of the last stage as detection data, a comparator that obtains a path having a minimum path metric from the surviving paths to each state obtained by the metric calculator, And a selector for inputting a data sequence D output by the comparator, selecting a data sequence corresponding to a path giving the minimum path metric obtained by the comparator, and outputting the selected data sequence to the feedback filter, wherein the feedback filter An information reproducing apparatus using a feedback filter, wherein a compensation amount for equalization is obtained based on a data sequence selected by the selector. 2. An information reproducing apparatus using a feedback filter according to claim 1, wherein the path memory length is shorter than the number of input data of the feedback filter, and the path memory holds the detection data output and feeds back the data. An information reproducing apparatus using a feedback filter, comprising a delay element for outputting to a filter. 3. An information reproducing apparatus using the feedback filter according to claim 1, wherein the selector corresponds to a path having a minimum path metric from among equalization errors corresponding to each surviving path. An information reproducing apparatus using a feedback filter characterized by selecting an equalization error, and performing adaptive equalization of a feedforward filter and a feedback filter using the selected equalization error. 4. An information reproducing apparatus using a feedback filter according to claim 1, wherein said feedback filter and metric calculator have a tree depth γ of 2, and said metric calculator has said feed depth. An information reproducing apparatus using a feedback filter, wherein maximum likelihood detection is performed by associating a two-state transition diagram with a reproduced waveform on which a forward filter output and a feedback filter output are superimposed. 5. An information reproducing apparatus using the feedback filter according to claim 1, wherein the feedback filter and the metric calculator have a tree depth γ of 3, and the metric calculator has a tree depth γ of 3. An information reproducing apparatus using a feedback filter, wherein maximum likelihood detection is performed by making a state transition diagram of four states correspond to a reproduced waveform on which a feedforward filter output and a feedback filter output are superimposed. 6. An information reproducing apparatus using the feedback filter according to claim 1, wherein the feedback filter and the metric calculator have a tree depth γ of 4, and the metric calculator has a tree depth γ of 4. An information reproducing apparatus using a feedback filter, wherein maximum likelihood detection is performed by associating an 8-state state transition diagram with a reproduced waveform on which a feedforward filter output and a feedback filter output are superimposed.