JP4545684B2 - Decoding device, playback device, decoding method, decoding program, and recording medium therefor - Google Patents

Description

  The present invention relates to a decoding device that decodes encoded information, a decoding method, a decoding program and a recording medium thereof, and a playback device that includes the decoding device.

  In recent years, as various types of information including image information, audio information, programs, and the like are digitized, the amount of digital information stored in a storage device has been dramatically increased. Along with this, development of storage devices suitable for increasing the capacity and increasing the density has been promoted.

  By the way, if an error is included in information (reproduction signal) read out from the storage device and reproduced, various problems occur due to the error. For example, if the stored information is a program, the computer cannot perform the intended operation. In addition, when the stored information is image information, the image quality is degraded.

  For this reason, conventionally, an error correction circuit for correcting an error is incorporated in a storage device using an optical disk, a hard disk or the like as a recording medium.

  As a method for decoding and error correction, for example, iterative decoding methods such as turbo codes and LDPC (Low Density Parity Check) codes have been proposed. In these iterative decoding methods, an error correction capability close to the theoretical characteristic limit (Shannon limit) can be obtained by repeatedly applying decoding processing to the obtained reproduced signal.

  In the iterative decoding method, the S / N or σ (standard deviation) value of the communication path is required for decoding calculation. Patent Document 1 discloses a method for obtaining an S / N or σ value.

  A conventional decoding device will be described below. FIG. 18 is a block diagram showing a configuration of a decoding apparatus using a conventional iterative decoding method.

  As shown in the figure, the conventional decoding apparatus includes a decoding circuit 104, an error rate calculation circuit 112, a controller 114, and a σ setting circuit 113.

The decoding circuit 104, is input reproduced signal y _n read from the information storage medium, and outputs the error rate calculating circuit 112 performs decoding processing of the reproduction signal y _n.

  As a decoding process performed in the decoding circuit 104, various conventionally proposed methods are used. Here, an example in the case of using the sum-product method described in Non-Patent Document 1 will be described. In the sum-product method, variable node processing and check node processing are repeatedly executed to obtain the posterior probability ratio. First, in the check node process, the calculation of equation (1) is performed.

  Here, sign (x) is a function that takes a value of +1 if x is positive, -1 if x is negative, and 0 if x is 0. F (x) is defined by the following equation (2).

  On the other hand, the variable node process is performed using the following equation (3).

  Here, λn is a log likelihood ratio (LLR) calculated from the received word, and is defined by the following equation (4).

_{Here, P} (y n _{| x} n = 0), when the recorded data _{x n} is 0, which indicates the probability of reproduction signal _{y n} is obtained.

After sufficiently repeating the process of alternately calculating α _mn and β _mn represented by the above formulas (1) and (3), an approximate value Q _n of the log posterior probability ratio is obtained as the following formula (5). It is done.

Further, when the sign of Q _n is positive, the bit estimation value is 0, and when the sign is negative, the bit estimation value is 1. In this way, the reproduction signal is decoded. For detecting the end of iterative calculation, for example, there are a method using parity and a method of adding a CRC code. In either method, when it is detected that there is no error by parity or CRC, the iterative calculation is terminated.

  Next, how to obtain the two probabilities used in the above equation (4) will be described.

As described _{above, P} (y n _{| x} n = 0), when the recorded data _{x n} is 0, which indicates the probability of reproduction signal _{y n} is obtained. Therefore, the distribution of the reproduced signal of the data 0 is assumed to be a normal distribution of the average value of -1, the probability that the reproduced signal becomes y _n is represented by the following formula.

Here, σ is a standard deviation.

Similarly, the distribution of the reproduced signal of the data 1 is assumed to be a normal distribution of the average value of -1, the probability that the reproduced signal becomes y _n is represented by the following formula.

At this time, λ _n can be expressed as the following equation (8).

  The error rate calculation circuit 112 calculates a bit error rate (bER) based on the decoding result of the decoding circuit 104 and outputs it to the controller 114.

  The controller 114 calculates the optimum σ from the set standard deviation σ and bER. Furthermore, the controller 114 instructs the σ setting circuit 113 to reset the optimal σ. Thereafter, the decoding process is performed with the optimal σ that has been reset.

Here, a process for obtaining the optimum standard deviation σ in the controller 114 will be described. The controller 114 measures bER while changing σ. FIG. 19 is a graph showing an example of measurement results. Here, ERH is an allowable upper limit error rate. The maximum value H and the minimum value L of σ satisfying this are obtained, and the average value is set as the optimum σ.
JP 2004-96481 A (publication date: March 25, 2004) Wadayama, Tadashi, “LDPC code and sum-product decoding”, Mathematical Sciences 497, published by Science Inc., October 20, 2004, pp. 36-41

  In the above conventional technique, since bER is measured while changing σ, it is necessary to execute a number of decoding processes until an optimum σ is obtained. For example, when 10 points need to be measured to obtain the curve shown in FIG. 19, 10 decoding processes are required.

Further, when σ in the distribution of the reproduction signal of x _n = 0 and x _n = 1 is different, it is necessary to measure bER by changing σ for each. Also in this case, if 10 points of measurement are required, 10 × 10 = 100 times of measurement are required.

  In this case, since the obtained result is not a curve as shown in FIG. 19 but a curve having two σ as variables, it is very difficult to calculate the optimum σ.

  The present invention has been made in view of the above problems, and an object of the present invention is to provide a decoding device, a decoding method, a decoding program, a recording medium thereof, and a recording medium that can quickly decode encoded information. An object of the present invention is to provide a playback device including a decoding device.

In order to solve the above-described problem, the decoding device of the present invention is a decoding device that decodes an encoded data signal sequence, and a statistic indicating variation in a signal included in the data signal sequence is represented by the data It is characterized by comprising: a statistic calculating unit that calculates based on a signal sequence; and a decoding unit that decodes the data signal sequence using the statistic calculated by the statistic calculating unit. Here, the statistic indicating the variation of the signal included in the data signal sequence is, for example, the variance σ ² , standard deviation σ, S / N ratio, etc. of the signal included in the data signal sequence.

  In a conventional decoding device, an optimum σ is obtained by performing a decoding process based on a predetermined standard deviation σ to calculate a bit error rate, and then repeatedly performing a process of calculating the bit error rate while changing σ. Was calculated and decrypted.

  On the other hand, in the above configuration, a statistic indicating variation in signals included in the data signal sequence is calculated based on the data signal sequence decoded by the statistic calculation unit, and the decoding unit calculates the statistic calculation unit. The data signal sequence is decoded using the statistics. For this reason, it is not necessary to repeat the decoding process in order to calculate the optimum σ as in the prior art (since there is no need to perform many error rate measurements), the decoding can be performed quickly. That is, as in the past, the i-th decoding process (i is a natural number) is performed, the value of σ is changed after waiting for the result of the i-th decoding process, and the i + 1-th decoding process is performed. Therefore, the decoding process can be performed quickly.

  Further, the statistic calculation means determines a signal level of a signal included in the data signal sequence and a plurality of calculation means for calculating a statistic indicating variation of the input signal, and according to the determined signal level And a data discriminating unit that distributes the signal to any one of the plurality of calculating units.

  According to the above configuration, the data discriminating unit discriminates the signal level of the signal included in the data signal sequence to be decoded, and distributes the signal to any of the plurality of calculating units according to the discriminated signal level. As a result, when the data signal sequence to be decoded is binary or multilevel data, each signal is distributed to one of the calculation means according to the signal level, and a statistic indicating variation for each signal level is obtained. Can be calculated. A decoding process with high accuracy can be performed by performing decoding using the statistics for each signal level thus calculated.

  The data discriminating unit compares the signal included in the data signal sequence with a preset temporary threshold value to classify each signal into a plurality of temporary signal levels, and the first comparing unit. Threshold value calculation means for calculating a threshold value based on each provisional signal level classified by the comparison means, and the signal included in the data signal sequence is compared with the threshold value calculated by the threshold value calculation means. And a second comparing means for determining the signal level of each signal.

  According to the above configuration, the first comparing means classifies each signal included in the data signal sequence to be decoded using a preset temporary threshold into a plurality of temporary signal levels, and the threshold calculating means A threshold value is calculated based on each provisional signal level classified by the first comparison means. Then, the second comparison means determines the signal level of each signal included in the data signal sequence to be decoded using the threshold value calculated by the threshold value calculation means. As a result, it is possible to calculate the statistic indicating the variation of the signals included in the data signal sequence with higher accuracy than when only the preset threshold value is used. Even if the provisional threshold value is deviated from the optimum value, the influence on the error rate can be reduced, and the above-mentioned statistics can always be calculated with high accuracy.

  In the above configuration, an average value calculating unit that calculates an average value of the provisional signal levels classified by the first comparison unit is provided, and the threshold value calculating unit includes each temporary value calculated by the average value calculating unit. The threshold value may be calculated based on the average value of the signal level.

  According to said structure, an average value calculation means calculates the average value of each temporary signal level classified by the 1st comparison means, and the said threshold value calculation means calculates the said threshold value based on this average value . As described above, by adopting a configuration in which the threshold value is calculated based on the average value of the temporary signal levels, it is possible to calculate the statistic indicating the variation of the signals included in the data signal sequence with higher accuracy.

  The data discriminating means includes a data generating means for generating the same signal as the statistic calculation signal included in the data signal sequence, and a signal included in the data signal sequence based on the signal generated by the data generating means. And a selection means for determining the signal level.

  According to the above configuration, it is possible to accurately determine the signal level of the signal included in the data signal sequence regardless of the quality of the data signal sequence to be decoded. In addition, since the process for determining the signal level using the threshold value is not involved, the threshold value does not affect the calculation accuracy of the statistic, and the statistic can always be calculated accurately.

  The statistic calculation means is included in the data signal sequence and probability calculation means A for calculating a probability that the signal level of the signal included in the data signal sequence is equal to or lower than a preset reference value SL. Included in the data signal sequence based on the probability calculation means B for calculating the probability that the signal level of the signal is equal to or lower than a preset reference value SH, and the probability calculated by the probability calculation means A and the probability calculation means B It is good also as a structure provided with the calculation means which calculates the statistic which shows the dispersion | variation in the signal to be performed.

  According to the above configuration, the probability calculating unit A calculates the probability that the signal level of the signal included in the data signal sequence is equal to or less than the preset reference value SL, and the probability calculating unit B is included in the data signal sequence. The probability that the signal level of the received signal is equal to or less than a preset reference value SH is calculated. Then, the calculation means calculates a statistic indicating the variation of the signals included in the data signal sequence based on the probabilities calculated by the probability calculation means A and the probability calculation means B. As a result, the statistic can be calculated directly from the data signal sequence to be decoded, so that the statistic can be calculated accurately.

  Further, the statistic calculation means includes first probability calculation means for calculating a probability that a signal belonging to the first signal level among signals included in the data signal sequence is equal to or lower than a first reference value set in advance; Second probability calculating means for calculating a probability that a signal belonging to the first signal level is equal to or lower than a preset second reference value among signals included in the data signal sequence; and a signal included in the data signal sequence Of these, a third probability calculating means for calculating a probability that a signal belonging to the second signal level is greater than or equal to a preset third reference value; and a signal belonging to the second signal level among the signals included in the data signal sequence. A fourth probability calculating means for calculating a probability equal to or higher than a preset fourth reference value; and a signal belonging to the first signal level based on the probabilities calculated by the first probability calculating means and the second probability calculating means. Roses A first calculation means for calculating a statistic indicating a signal, and a statistic indicating a variation of the signal belonging to the second signal level based on the probabilities calculated by the third probability calculation means and the fourth probability calculation means. The structure provided with the 2nd calculation means may be sufficient.

  According to the above configuration, the statistic indicating the variation of the signal belonging to the first signal level and the statistic indicating the variation of the signal belonging to the first signal level can be directly calculated from the data signal sequence to be decoded. Therefore, for example, when calculating a statistic indicating a variation in each signal level using a threshold, the statistic can be accurately calculated without being affected by a deviation from the optimum value of the threshold. . Further, even when the distribution of signals belonging to the first signal level and the distribution of signals belonging to the second signal level partially overlap, the above-mentioned statistics of the signals belonging to each signal level can be accurately calculated.

  The statistic calculation means includes: a differential detection means for differentially detecting the data signal sequence; an absolute value calculation means for calculating an absolute value of a detection result of the differential detection means; and an absolute value calculation means. It is good also as a structure provided with the calculation means which calculates the said statistics based on the calculated absolute value.

  According to said structure, the said statistics can be directly calculated from the data signal sequence to decode. Therefore, for example, when calculating a statistic indicating a variation in each signal level using a threshold, the statistic can be accurately calculated without being affected by a deviation from the optimum value of the threshold. .

  Further, the processing for sequentially calculating the statistics for each signal included in the data signal sequence by the statistics calculation means and the processing for sequentially decoding the signals included in the data signal sequence by the decoding means are performed in parallel. It is good also as composition to do.

  According to the above configuration, since it is not necessary to repeatedly perform the decoding process in order to calculate the optimum σ as in the prior art, the decoding process can be performed quickly.

  In order to solve the above-described problems, the reproducing apparatus of the present invention includes reproducing means for reading information recorded on an information recording medium and any one of the decoding apparatuses described above. For this reason, the data signal sequence read from the information recording medium can be quickly decoded.

  In order to solve the above-described problem, the decoding method of the present invention is a decoding method for decoding an encoded data signal sequence, wherein a statistic indicating variation in a signal included in the data signal sequence is represented by the data The method includes a statistic calculation step that is calculated based on a signal sequence, and a decoding step that decodes the data signal sequence using the statistic calculated in the statistic calculation step.

  According to the above decoding method, it is not necessary to repeatedly perform the decoding process in order to calculate the optimum σ as in the prior art, so that decoding can be performed quickly.

  The decoding device may be realized by a computer. In this case, a decoding program that causes the decoding device to be realized by the computer by causing the computer to operate as the above-described means, and a computer-readable program that records the decoding program. Such recording media are also included in the scope of the present invention.

  As described above, the decoding apparatus according to the present invention includes a statistic calculation unit that calculates a statistic indicating variation in a signal included in the data signal sequence based on the data signal sequence, and a calculation performed by the statistic calculation unit. Decoding means for decoding the data signal sequence using the statistics.

  In addition, the reproduction method of the present invention includes a statistic calculation step for calculating a statistic indicating variation in a signal included in the data signal sequence based on the data signal sequence, and a statistic calculated in the statistic calculation step. And a decoding step of decoding the data signal sequence using.

  Therefore, it is not necessary to repeat the decoding process in order to calculate the optimum σ as in the prior art, so that decoding can be performed quickly.

[Embodiment 1]
An embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a block diagram showing the configuration of a playback apparatus (information storage medium playback apparatus) 100 according to this embodiment.

  As shown in this figure, the reproducing apparatus 100 includes a medium 1, a reproducing head 2, an equivalent circuit 3, a decoding circuit 4, a data discriminating circuit 5, a variance calculating circuit 6, and a variance calculating circuit 7. The decoding circuit 4, the data discriminating circuit 5, the variance calculating circuit 6, and the variance calculating circuit 7 constitute a decoding device according to this embodiment.

  A medium (information recording medium) 1 is a carrier for recording information. The configuration of the medium 1 is not particularly limited, but a hologram storage medium is used in the present embodiment. A hologram recording medium performs recording by applying strong light to a recording layer during recording and changing the material of the recording layer (volume recording material) to create interference fringes.

  The reproducing head (reproducing means) 2 reads information recorded on the medium 1 and generates a reproduction signal. The reproducing head 2 includes an image sensor (not shown), reads information including two-dimensional page data recorded on the hologram storage medium by the image sensor, and generates a reproduction signal of the two-dimensional page data. . For example, a CCD element or a CMOS element is used as the imaging element. Further, the reproducing head 2 outputs the generated reproduction signal to the equivalent circuit 3.

  The equivalent circuit 3 equalizes the waveform of the reproduction signal input from the reproduction head 2. Two-dimensional signal processing is also performed in this equalization processing. The two-dimensional equalization process is realized by a two-dimensional filter that is generally used in image processing or the like. In addition, the equivalent circuit 3 outputs the page data subjected to the equivalent process to the decoding circuit 4 and the data determination circuit 5.

  The decoding circuit 4 performs a decoding process of the equivalent processed page data. In the present embodiment, information encoded using the LDPC code is decoded by the decoding circuit 4 by LDPC decoding.

  The data discriminating circuit 5 discriminates the signal level of the equalized page data. In the present embodiment, it is assumed that data is recorded at a level of 0 or 1. Therefore, the page data is divided into 0 or 1 by the data discrimination circuit 5. That is, the data discriminating circuit 5 outputs data (data 0) estimated to be 0 level to the variance calculation circuit 6 and outputs data (data 1) estimated to be 1 level to the variance calculation circuit 7.

The variance calculation circuit 6 and the variance calculation circuit 7 calculate the variance σ ² of the input data, respectively. The variance σ ₀ ² of the 0 level data calculated by the variance calculation circuit 6 and the variance σ ₁ ² of the 1 level data calculated by the variance calculation circuit 7 are both output to the decoding circuit 4, and the decoding circuit 4 performs the decoding process. Used for.

  Next, the decoding process in the decoding circuit 4 will be described. Various methods have been proposed for decoding processing, and the decoding processing method used in the present embodiment is not particularly limited. Here, the sum-product method described in Non-Patent Document 1 is used. The case of using will be described.

  In the sum-product method, variable node processing and check node processing are repeatedly executed to obtain the posterior probability ratio. First, in the check node process, the following equation (7) is calculated.

  Here, sign (x) is a function that takes a value of +1 if x is positive, -1 if x is negative, and 0 if x is 0. F (x) is defined by the following equation (8).

  On the other hand, the variable node process is performed using the following equation (9).

Here, λ _n is a log likelihood ratio (LLR) calculated from the received word, and is defined by the following equation (10).

_{Here, P} (y n _{| x} n = 0), when the recorded data _{x n} is 0, which indicates the probability of reproduction signal _{y n} is obtained.

After sufficiently repeating the process of alternately calculating α _mn and β _mn represented by the above equations (7) and (9), an approximate value Q _n of the log posterior probability ratio is obtained as the following equation (11).

Further, when the sign of Q _n is positive, the bit estimation value is 0, and when the sign is negative, the bit estimation value is 1. In this way, the reproduction signal is decoded. In order to detect the end timing of the iterative calculation, for example, a method using parity or a method of adding a CRC code can be used. In any case, the iterative calculation is terminated when it is detected by parity or CRC that there is no error.

Next, how to obtain the two probabilities used in the above equation (10) will be described. As described _{above, P} (y n _{| x} n = 0), when the recorded data _{x n} is 0, which indicates the probability of reproduction signal _{y n} is obtained. It is assumed that the distribution of the reproduction signal of data 0 is a normal distribution with 0 as an average value. In other words, it is assumed the reproduction signal y _n is obtained by adding the Gaussian noise in the recording data x _n. In this case, the probability that the reproduced signal becomes y _n is represented by the following formula.

Here, σ ₀ is a standard deviation of data where x _n = 0.

Similarly, assuming that the distribution of the reproduced signal of data 1 is a normal distribution of the average value of 1, the probability that the reproduced signal becomes y _n is represented by the following formula.

Here, σ ₁ is the standard deviation of data with x _n = 1.

At this time, λ _n can be expressed as in equation (12).

FIG. 2 is a graph showing an example of the frequency of occurrence of data 0 and data 1 in the reproduction signal. As shown in this figure, in the hologram storage medium, σ ₀ and σ ₁ are generally different. For this reason, it is necessary to individually obtain σ ₀ and σ ₁ .

As shown in equation (12), the distribution of the reproduced signal is assumed to be normally distributed, by determining the sigma ₀ ² and sigma ₁ ^2, can be calculated lambda _n.

In the reproducing apparatus 100, the variance calculating circuit 6 calculates the sigma ₀ ^2, variance calculation circuit 7 is adapted to calculate the sigma ₁ ^2.

Regarding the calculation method of σ ₀ ² and σ ₁ ² , the data discrimination circuit 5 discriminates whether the reproduction signal is 0 or 1, outputs the data discriminated as 0 to the variance calculation circuit 6, and determines the data discriminated as 1 Is output to the dispersion calculation circuit 7, the dispersion can be easily calculated in each dispersion output circuit. In this case, in order to accurately obtain the variance, it becomes a problem how the data discrimination circuit 5 discriminates between 0 and 1.

  However, as in the example shown in FIG. 2, the upper side of the distribution of data 0 (the higher signal level) and the lower side of the distribution of data 1 (the lower signal level) overlap. In the case where the threshold value is 0, the general method for discriminating between 0 and 1 changes the dispersion value obtained depending on where the threshold value is set. In general, since the reproduction signal includes noise, such a phenomenon that the distribution bases overlap each other cannot be avoided.

  Therefore, in the reproducing apparatus 100 according to the present embodiment, 0 and 1 can be accurately discriminated by the data discriminating circuit 5 even when part of the distribution of data 0 and data 1 overlap.

  FIG. 3 is a block diagram showing a configuration of the data discrimination circuit 5. As shown in this figure, the data discrimination circuit 5 includes a comparison circuit 51, a temporary data 1 average value calculation circuit 52, a temporary data 0 average value calculation circuit 53, a threshold value calculation circuit 55, and a comparison circuit 54.

Comparator circuit 51 compares the reproduced data y _n output from the equivalent circuit 3 and a temporary threshold SL 0. The provisional threshold value SL0 is a value set in advance so as to be approximately the center level of the data 0 and data 1 levels, for example. The reproduction signal level varies depending on the characteristics of the medium 1 and the reproduction head 2. Therefore, the temporary threshold value SL0 may be a value slightly deviated from the true center level.

Comparison circuit 51, based on the result of comparing the reproduced data y _n and the temporary threshold SL 0, to determine whether the data 1 is data 0 for each bit of the reproduced data y _n (tentative decision). The bits determined to be data 0 (temporary data 0) are output to the temporary data 0 average value calculation circuit 53, and the bits determined to be data 1 (temporary data 1) are calculated to the temporary data 1 average value. Output to the circuit 52.

  The temporary data 0 average value calculation circuit 53 calculates the average value M0 of the data 0 input from the comparison circuit 51 and outputs it to the threshold value calculation circuit 55. The temporary data 1 average value calculation circuit 52 calculates the average value M1 of the data 1 input from the comparison circuit 51 and outputs the average value M1 to the threshold value calculation circuit 55.

  The threshold value calculation circuit 55 calculates a threshold value SL from the two average values M0 and M1 input from the temporary data 0 average value calculation circuit 53 and the temporary data 1 average value calculation circuit 52, and calculates the calculated threshold value. SL is output to the comparison circuit 54.

  Here, the data spread of data 0 and the data spread of data 1 are different, but when the variance is n times or less (n is an arbitrary number set in advance. Typically, 0 to 10). That is, when the larger variance is n times or less than the smaller variance, for example, the threshold value SL may be set to the median value of M0 and M1. When the variance difference is larger than n times, the threshold value may be set at a level close to the average level of the data having a smaller variance than the median.

For example, if the larger variance is less than n times the smaller variance,
SL = (M0 + M1) / 2,
If the larger variance exceeds n times the smaller variance,
SL = kM1 + (1-k) M0
And Here, k is, σ ₀ ² <σ _{1 0} when the ² <k <0.5, when the σ ₀ ^2> σ ₁ ² and 0.5 <k <1.0.

Comparison circuit 54, by using the threshold value SL input from the threshold calculating circuit 55, the reproduction signal y _n input from the equivalent circuit 3 determines whether a 1 or a 0. That is, when the reproduction signal y _n is greater than the threshold value SL is determined that data to be 1, it is determined that 0 otherwise. In this manner, the reproduction signal _{y n} is divided into 0 (DATA0) 1 and (DATA1), 0 and discriminated data to the variance calculation circuit 6, respectively 1 and determined data to the variance calculation circuit 7 Is output.

Note that the above-described calculation of variance σ ² needs to be performed for each LDPC decoding processing unit (hereinafter referred to as a block). The physical allocation method to the image on the image sensor of the block is not particularly limited, and several methods are conceivable. FIG. 4 is an explanatory diagram illustrating an example of a block allocation method. The grid-like small squares shown in this figure represent pixels of the image sensor, and a group of pixels emphasized by diagonal lines or horizontal lines represents blocks. In the example shown in this figure, three block patterns (block patterns A, B, and C) are drawn at the same time for explanation, but only one of them is actually used.

  The block pattern A is a method for assigning blocks along rows or columns on the image sensor. In this case, the row or the column (the extending direction of the block) matches the reading direction of the reproduction signal from the image sensor. That is, in the example of FIG. 4, the block allocation direction is the row direction, and the readout direction of the reproduction signal is also the row direction (lateral direction). As described above, by matching the extending direction of the block and the reading direction of the reproduction signal, the block data can be decoded in the order of the read data. Therefore, there is no need to reconstruct the data from the reproduction signal, so there is no need for a buffer memory for temporarily storing the data for reconstruction, and no processing circuit for reconstruction is necessary. Therefore, the signal processing circuit can be simplified.

  Block pattern B is a method of assigning a substantially square (rectangular) block on the image sensor. In this case, it is necessary to extract the data included in the block from the read data and reconstruct the data. There is an advantage that it is difficult to be affected by the light amount distribution in the image pickup element surface due to the optical system 1 or the optical system.

  Block pattern C is a method of assigning substantially concentric blocks on the image sensor. This makes the block data extraction and reconstruction process more complicated than the block pattern B, but has the advantage that it is less susceptible to the influence of the concentric light quantity distribution due to the non-uniformity of the optical system.

  As described above, each block pattern has advantages and disadvantages. Therefore, it is preferable to select each block pattern according to the characteristics of the medium to be used and the optical system. In addition, you may employ | adopt not only the above-mentioned three patterns but another block pattern.

Next, the timing of the variance calculation process and the decoding process will be described. FIG. 5A is a timing chart of the variance (σ ² ) calculation process and the decoding process in the playback device 100.

  First, when the reproduction signal of the block B1 is input from the equivalent circuit 3 to the data discriminating circuit 5 and the decoding circuit 4 at time t0, the variance calculation process of the block B1 is performed. In other words, the data discrimination circuit 5 discriminates the data, and the variance calculation circuits 6 and 7 calculate the variance.

  When the variance calculation process ends at time t1, the decoding circuit 4 starts decoding the block B1 using the calculated variance. The data discriminating circuit 5 and the variance calculation circuits 6 and 7 start the variance calculation process for the block B2 input next.

  The distribution calculation processing time t3 of the block B2 ends, but at this point, since the decoding processing of the block B1 has not been completed yet, the obtained distribution of the block B2 is held as it is. Note that storage means (memory or the like) for holding the variance may be provided in each of the variance calculation circuits 6 and 7, or may be provided in the decoding circuit 4. 7 and the decoding circuit 4 may be provided separately.

  When the decoding process for the block B1 ends at time t4, the decoding circuit 4 starts the decoding process for the block B2 using the previously obtained distribution of the block B2. Further, the data discriminating circuit 5 and the variance calculation circuits 6 and 7 start the variance calculation processing of the block B3 inputted next.

  In this way, by performing the variance calculation processing and the decoding processing in parallel, the waiting time until the decoding processing for variance calculation is started can be reduced from the time t0 which is the start time of the variance calculation processing to the first block. Only the period up to time t1, which is the time when the variance calculation process ends, can be limited.

  In the example of FIG. 5 (a), after obtaining the distribution of block B2 at time t3, the decoding process of block B1 ends (the decoding process of block B2 is started) until time t4. Although the start of the calculation process is waited for, the present invention is not limited to this.

  For example, the calculated block variance is stored in a storage means (memory or the like), and as shown in FIG. 5B, when the variance calculation processing for one block is completed, the variance calculation processing for the next block is continuously performed. You may make it perform. In this case, the variance calculation process for each block is performed continuously rather than intermittently. Further, the timing for starting the variance calculation process for the next block may be adjusted according to the capacity of the storage means for storing the variance calculation result. However, in any case, the point that the reproduction of data is not completed until all the decoding processes are completed remains the same.

  Next, an experimental result obtained by performing a decoding process using the playback device 100 will be described. FIG. 6 is a graph showing the result of measuring the bit error rate (bER) while changing the SNR (S / N ratio). The code length of the LDPC code is 512 bits, and the coding rate is 0.87. Further, the comparison results shown in the figure show the results of performing the decoding process using the distribution of only data 0 or data 1.

  As shown in this figure, by using the playback apparatus 100, the bER can be greatly improved as compared with the comparison result. That is, in the case of using a hologram storage medium, bER can be reduced by calculating the variance of data 0 and data 1, respectively, and performing decoding processing using them.

  FIG. 7 is a graph showing the distribution of data 0 and data 1 when SNR = 10.2 dB in the above experimental results. As described above, it will be described below that a good decoding result can be obtained by the reproducing apparatus 100 even when the two distributions overlap.

  FIG. 8 is a graph showing the effect of improving the allowable range of the threshold for discriminating two data by the playback apparatus 100.

  As described above, the playback apparatus 100 once discriminates between data 0 and data 1 using the temporary threshold value (temporary determination), and calculates the threshold value based on the respective average values. Further, the final discrimination between data 0 and data 1 is performed using the threshold value. The graph shown as “Result” in FIG. 8 is an experimental result by the reproducing apparatus 100, and the threshold value indicates the provisional threshold value.

  As shown in this figure, in the reproducing apparatus 100, even when the temporary threshold value deviates from the optimum value (0.5), the influence on the bER is small. Specifically, in the playback apparatus 100, the temporary threshold value is between 0.4 and 0.6 (about ± 10% of the difference between the original signal levels of the two signals). Even if it changes, bER is hardly affected. Even when the provisional threshold value changed more, bER was relatively less deteriorated.

  On the other hand, the graph shown as “comparison result” shows the result when data 0 and data 1 are discriminated using only a preset threshold value without using a temporary threshold value.

  As shown in this figure, in the case of the comparison result, when the threshold value deviates from the optimum value (0.5), the bER is greatly deteriorated.

  Thus, in the reproducing apparatus 100, even if the setting value of the temporary threshold value deviates from the optimum value, the deterioration of bER can be suppressed as compared with the conventional case. Further, if the deviation of the temporary threshold is within ± 10% of the difference between the original signal levels of the two signals, a bER substantially the same as when using the optimum threshold can be obtained. .

  Next, the validity of the dispersion obtained in the playback apparatus 100 will be described. In the above experiment, when SNR = 10.2 dB, the variance of data 1 calculated by the playback apparatus 100 was 0.3, and the variance of data 0 was 0.13. Moreover, bER at that time was 1.8E-3.

  On the other hand, FIG. 9 is a graph showing the result of measuring the bER for all combinations of the variance of data 1 and the variance of data 0 (should all shake the combinations manually). As shown in this figure, the minimum value (optimum value) of bER is 1.8E-3. When this bER is given, the variance of data 1 is 0.3 and the variance of data 0 is 0. It was 15. This result almost coincides with the calculation result of the playback apparatus 100. Therefore, it can be seen that the playback apparatus 100 can perform a highly accurate decoding process.

  As described above, according to the playback apparatus 100 according to the present embodiment, the waiting time until the decoding process for variance calculation is started can be shortened, and the time required for playback can be shortened by performing the decoding process quickly.

  Further, the variance can be calculated accurately, and the best bit error rate (bER) can be obtained. That is, errors can be reduced by optimizing bER.

  Furthermore, since the allowable range of deviation from the optimum threshold value (provisional threshold value) set in advance for discriminating the reproduction signal into two signal levels can be increased, a device more suitable for practical use can be obtained. realizable.

  In this embodiment, the case where the reproduction signal has two signal levels of 0 and 1 has been described. However, the present invention is not limited to this, and a configuration in which the signal level is classified into a larger number of signal levels may be used. Also in this case, the reproduction signal is classified into a plurality of signal levels (provisional signal levels) based on the temporary threshold value, and the threshold is determined based on each signal level (for example, based on the average value of each temporary signal level). By calculating the value and comparing the threshold value thus calculated with the reproduction signal to determine the signal level of the reproduction signal, the same effect as described above can be obtained.

  In this embodiment, the temporary data 0 average value calculation circuit 53 and the temporary data 1 average value calculation circuit 52 calculate the average values of the temporary data 1 and the temporary data 0, respectively, and based on these average values, the threshold value is calculated. Although the calculation circuit 55 calculates the threshold value, the present invention is not limited to this. For example, the threshold value may be calculated using a median value of the temporary data 1 and the temporary data 0, an average value of a part of the temporary data, and the like.

[Embodiment 2]
Another embodiment of the present invention will be described. For convenience of explanation, members having the same functions as those described in the first embodiment are denoted by the same reference numerals, and description thereof is omitted.

  FIG. 10 is a block diagram showing a configuration of a playback apparatus (information storage medium playback apparatus) 100b according to the present embodiment. As shown in this figure, the reproducing apparatus 100b includes a distributed arithmetic circuit 8 instead of the data discriminating circuit 5 and the dispersion calculating circuits 6 and 7 in the reproducing apparatus 100 shown in the first embodiment. Note that the decoding circuit 4 and the distributed arithmetic circuit 8 constitute a decoding device according to the present embodiment.

FIG. 11 is a block diagram showing the configuration of the distributed arithmetic circuit 8. In reproduction apparatus 100b, the dispersion calculation circuit 8, without performing the data determination process, and obtains the distributed directly from the reproduction signal y _n.

As shown in FIG. 11, the distributed arithmetic circuit 8 includes probability detection circuits 81 to 84, a σ ₀ calculation circuit 85, and a σ ₁ calculation circuit 86.

  The probability detection circuit 81 calculates a probability RA that data 0 (signal belonging to the first signal level) is S0L or less, and the probability detection circuit 82 calculates a probability RB that data 0 is S0H or less. . The probability detection circuit 83 calculates the probability RC that the data 1 (signal belonging to the second signal level) is S1L or more, and the probability detection circuit 84 calculates the probability RD that the data 1 is S1H or more. It is.

  The values of S0L, S0H, S1L, and S1H are not particularly limited, and may be set as appropriate according to the characteristics of the medium 1 and the optical system.

However, with respect to S0L and S0H, the value is smaller than the peak of the distribution of data 0 and the number of data with S0L or less is 10% or more, that is, 0.1 ≦ RA <RB <0.5. It is preferable to set so as to satisfy the relationship. If RA and RB are within this numerical range, the variance σ ₀ ² can be calculated with sufficient accuracy.

Similarly, for S1L and S1H, the value is larger than the peak of the distribution of data 1 and the number of data exceeding S1H is 10% or less, that is, 0.5 <RC <RD ≦ <0. It is preferable to set so as to satisfy the relationship of 9. If RC and RD are within this numerical range, the variance σ ₁ ² can be calculated with sufficient accuracy. Therefore, the allowable ranges of S0L, S0H and S1L, S1H for calculating the variances σ ₀ ² and σ ₁ ² with sufficient accuracy in the present embodiment are the same as those in the first embodiment with the variances σ ₀ ² and σ. wider than the allowable range of the temporary threshold SL0 for calculating the ₁ ^2.

  FIG. 12 is a graph showing an example of the relationship between the distribution of the reproduction signal and S0L, S0H, S1L, S1H.

  A probability calculation method in the probability detection circuits 81 to 84 will be specifically described. The probability detection circuit 81 counts the number of data that is less than or equal to the threshold value S0L and divides by the total number of data 0. Here, an approximate value can be used as the total number of data 0. For example, when data in which data 0 and data 1 appear at random (for example, user data indicating user's personal information) is recorded on the medium 1 as it is, the appearance probability of data 0 and data 1 is regarded as 0.5. Therefore, half of the total number of data may be the total number of data 0. Further, when data subjected to some modulation processing is recorded on the medium 1 or when some data is subjected to data read from the medium 1, the appearance probability of data 0 determined by the modulation rule is multiplied by the total number of data. Thus, the total number of data 0 is obtained.

  Similarly, the probability detection circuits 82 to 84 calculate the probability RB that the data 0 is S0H or less, the probability RC that the data 1 is S1L or more, and the probability RD that the data 1 is S1H or more.

The σ ₀ calculation circuit 85 calculates the variance σ ₀ ² of the data 0 based on the probabilities RA and RB, and the σ ₁ calculation circuit 86 calculates the variance σ ₁ ² of the data 1 based on the probabilities RC and RD. Is.

  If the distribution of data 0 and data 1 is a normal distribution, the above probabilities RA and RB can be expressed by the following equations (13) and (14).

Here, there are two unknowns, σ ₀ and μ ₀ , and there are two equations (13) and (14). Therefore, in the σ ₀ calculation circuit 85, simultaneous equations (13) and (14) By solving the equation, σ ₀ and μ ₀ can be easily obtained. Then, the σ ₀ calculation circuit 85 calculates the variance σ ₀ ² by squaring the σ ₀ calculated in this way, and outputs it to the decoding circuit 4.

  The probabilities RC and RD can be expressed as the following equations (15) and (16), assuming that the distribution of data 0 and data 1 is a normal distribution.

Similar to the σ ₀ calculation circuit 85, the σ ₁ calculation circuit 86 calculates σ ₁ and μ ₁ based on the probabilities RC and RD, calculates the variance σ ₁ ² by squaring the calculated σ _1, and performs decoding. Output to circuit 4.

  As described above, the playback device 100b does not include the process of discriminating between data 0 and data 1 using a preset threshold value as in the first embodiment, so that the distribution of data 0 and data 1 is not included. Even when there is an overlap, the variance between the two can be calculated without being affected by the set value of the threshold.

  Even when there is an overlap in the distribution of data 0 and data 1, accurate dispersion can be obtained as compared with the reproducing apparatus 100 according to the first embodiment. That is, when the distribution of data 0 and the distribution of data 1 overlap, in the method of separating 0 and 1 by the threshold value, the data that should originally be 0 is determined to be 1 or the data that should originally be 1 An error may occur due to being determined to be zero. On the other hand, in the present embodiment, since a threshold value that causes an error is not used, the variance can be calculated more accurately than in the first embodiment.

  Further, in the playback device 100b, as in the playback device 100 according to the first embodiment, since the process of changing the σ and measuring the bER is not performed, the variance can be calculated more quickly than in the past.

  Note that the playback apparatus 100b needs to solve simultaneous equations including statistical functions, and thus the circuit configuration is more complicated than the playback apparatus 100 according to the first embodiment. Therefore, either the method shown in the first embodiment or the method according to the present embodiment may be selected according to the required dispersion accuracy and the allowable circuit scale.

[Embodiment 3]
Still another embodiment of the present invention will be described. For convenience of explanation, members having the same functions as those described in the first and second embodiments are denoted by the same reference numerals and description thereof is omitted.

  The reproduction apparatus according to the present embodiment is obtained by replacing the data determination circuit 5 in the reproduction apparatus 100 according to the first embodiment with a data determination circuit 5b shown in FIG. Other configurations are the same as those of the playback apparatus 100 according to the first embodiment. Therefore, the decoding circuit 4, the data discriminating circuit 5b, the variance calculation circuit 6, and the variance calculation circuit 7 constitute the decoding device according to the present embodiment.

  As shown in FIG. 13, the data determination circuit 5 b includes a selection circuit 56 and a data generator 57.

Or selection circuit 56, the reproduction signal y _n received as input, based on the value inputted from the data generator 57, and outputs from one output to each data as data 0 (output terminal of the data 0 (Data0 output) ) Or data 1 (whether the data 1 is output from the output terminal (Data 1 output)) is selected.

  The data generator 57 outputs a specific bit string (statistical amount calculation signal) to the selection circuit 56 using a Start signal supplied from a control unit (not shown) as a trigger. As a specific configuration, for example, bit string information stored in a memory element (not shown) may be read using a Start signal as a starting point. Alternatively, a bit string may be generated using a shift register.

  In this embodiment, it is assumed that the same bit pattern as the dispersion calculation bit pattern (statistic calculation signal) output from the data generator 57 is recorded in the medium 1 in advance. Therefore, when the output from the data generator 57 to the selection circuit 56 is 1, the data read from the medium 1 is selected to be 1, and when the output from the data generator 57 to the selection circuit 56 is 0, The data read from the medium 1 is selected to be zero. Note that the bit pattern that is recorded on the medium 1 and that is the same as the bit pattern output from the data generator 57 needs to be known data at the time of selection processing in the selection circuit 56. Therefore, this bit pattern needs to be data prepared in advance for use in dispersion detection, not user data or the like.

  Next, the timing for generating the Start signal will be described. FIG. 14 is a timing chart showing the timing for generating the Start signal.

  In the example of FIG. 14, a block CA of data for variance calculation is inserted at predetermined intervals i into blocks B1, B2,... Of user data (data to be recorded arbitrarily by the user). As described above, known information (bit pattern) is recorded in the block CA, and the recorded information is the same as the information obtained by the data generator 57. In the case of the example of FIG. 14, since the block CA is recorded at a predetermined interval i, the Start signal is also generated for each i accordingly.

  The number of data in each block CA is not necessarily the same as the number of data in each block B1, B2,.

  For example, as shown in FIG. 15, the number of data in each block CA may be smaller than the number of data in each block B1, B2,. In this case, since the number of data in each block CA is smaller than in the example of FIG. 14, the capacity of user data that can be recorded on the medium 1 (the total capacity of the blocks B1, B2,...) As shown in FIG. The frequency of appearance of the block CA can be increased without significantly reducing.

  In FIG. 15, a block CA is arranged at the head of each block B1, B2,. Therefore, the Start signal is generated for each of the blocks B1, B2,. In this case, since the number of data included in each block CA is small, the variance may be calculated using data included in a plurality of blocks CA. In addition, in order to remove the influence of short-term fluctuations such as spike noise, it is desirable that the number of data (the number of data in the block CA) used for the dispersion calculation is 100 or more.

  As described above, in the present embodiment, 0 or 1 of each data is not discriminated from the reproduction signal of the user data using the threshold value or the probability, but the known data (data for calculating the variance) is stored in the medium 1 in advance. ) Is recorded, and when the reproduction signal of the user data is reproduced, whether the reproduction signal of the user data is 0 or 1 is selected based on the dispersion calculation data recorded on the medium 1 together with the user data.

  This makes it possible to accurately select 0 or 1 regardless of the quality of the reproduction signal. However, since it is necessary to record the block CA of data for dispersion detection on the medium 1, there is a demerit that the storage capacity for recording user data is reduced and the transfer rate is lowered. Therefore, whether to use the method of the present embodiment or the method of the first or second embodiment may be determined in consideration of the storage capacity, transfer rate, etc. of necessary user data.

[Embodiment 4]
Still another embodiment of the present invention will be described. For convenience of explanation, members having the same functions as those described in the first to third embodiments are denoted by the same reference numerals and description thereof is omitted.

  FIG. 16 is a block diagram showing the configuration of the playback device 100d according to this embodiment. As shown in this figure, the reproducing apparatus 100d is different from the data discriminating circuit 5 and the variance calculating circuits 6 and 7 in the reproducing apparatus 100 shown in the first embodiment in that a differential circuit 9, an absolute value calculating circuit 10, and a variance calculation are performed. A circuit 11 is provided. Therefore, the decoding circuit according to the present embodiment is formed by the decoding circuit 4, the differential circuit 9, the absolute value calculation circuit 10, and the variance calculation circuit 11.

The differential circuit 9 performs a differential operation on the reproduction signal input from the equivalent circuit 3 and outputs the operation result to the decoding circuit 4 and the absolute value calculation circuit 10. The method of differential detection is not particularly limited. For example, 1 bit of user data is assigned to 2 bits of (0, 1) or (1, 0) on the medium 1, and the adjacent 0 and 1 can be used. In this case, as an ideal signal level obtained after differential,
0-1 = -1
1-0 = 1
It becomes two levels. Therefore, in this case, two distributions centering on -1 and 1 appear. However, unlike Embodiments 1 to 3 described above, the variance is the same at two levels as shown in FIG.

  The absolute value calculation circuit 10 inverts the sign of the distribution centered on −1 as shown in FIG. 17 to generate data superimposed on the distribution centered on 1, and outputs the data to the variance calculation circuit 11. To do.

  The variance calculation circuit 11 calculates one variance from all the data input from the absolute value calculation circuit 10 and outputs the calculation result to the decoding circuit 4.

  The decryption circuit 4 performs decryption calculation using the variance input from the variance calculation circuit 11. However, in the present embodiment, unlike the first embodiment, the same variance is used for both of the two distributions. For this reason, the decoding circuit 4 performs decoding calculation using λn calculated by the following equation (17).

  As described above, in this embodiment, the differential calculation is performed on the reproduction signal, and the variance of the two distributions is calculated by taking the absolute value of the result of the differential calculation. Decoding calculation is performed using one variance.

  For this reason, since the process of discriminating data using a threshold value is not included, even when there is an overlap between two distribution bases, the variance can be calculated appropriately without being influenced by the set value of the threshold value.

In each of the above-described embodiments, the example in which the variance σ ² is calculated and used as a statistic representing the variation in information has been described. However, the essence of the present invention is shown in the above equation (12) or the above equation (17). In order to calculate λn, a statistic indicating variation in information is obtained. Therefore, for example, S / N, σ, and the like may be obtained instead of the variance σ ² as a statistic representing the variation in information, and in that case, substantially the same effects as those of the above-described embodiments can be obtained. .

  In each of the above embodiments, the case where the reproduction signal has two signal levels of 0 and 1 has been described. However, the present invention is not limited to this.

  In each of the above embodiments, the playback apparatus that reads and plays back the information recorded on the medium 1 has been described. However, the present invention is not limited to this, and a signal input from an external device that is communicably connected by wire or wirelessly. It may be a playback device that plays back (decodes).

  Also, each block of the playback device in each of the above embodiments, in particular, the equivalent circuit 3, the data discrimination circuit 5, the variance calculation circuits 6 and 7, the decoding circuit 4, the variance calculation circuit 8, the data discrimination circuit 5b, the differential circuit 9, and the absolute The value calculation circuit 10, the variance calculation circuit 11, and each block included in them may be realized by hardware logic, or a part or all of these may be realized by software using a processor such as a CPU. It may be done.

  That is, the playback device according to each of the embodiments includes a CPU (central processing unit) that executes instructions of a control program that implements each function, a ROM (read only memory) that stores the program, and a RAM ( random access memory), a storage device (recording medium) such as a memory for storing the program and various data, and the like. In this case, an object of the present invention is to provide a recording medium on which a program code (execution format program, intermediate code program, source program) of a control program for a playback apparatus, which is software that realizes the above-described functions, is recorded so as to be readable by a computer. The program is supplied to the playback device, and the computer (or CPU or MPU) reads and executes the program code recorded on the recording medium.

  Examples of the recording medium include tapes such as magnetic tapes and cassette tapes, magnetic disks such as floppy (registered trademark) disks / hard disks, and disks including optical disks such as CD-ROM / MO / MD / DVD / CD-R. Card system such as IC card, IC card (including memory card) / optical card, or semiconductor memory system such as mask ROM / EPROM / EEPROM / flash ROM.

  Further, the playback device may be configured to be connectable to a communication network, and the program code may be supplied via the communication network. The communication network is not particularly limited. For example, the Internet, intranet, extranet, LAN, ISDN, VAN, CATV communication network, virtual private network, telephone line network, mobile communication network, satellite communication. A net or the like is available. Further, the transmission medium constituting the communication network is not particularly limited. For example, even in the case of wired such as IEEE 1394, USB, power line carrier, cable TV line, telephone line, ADSL line, etc., infrared rays such as IrDA and remote control, Bluetooth ( (Registered trademark), 802.11 wireless, HDR, mobile phone network, satellite line, terrestrial digital network, and the like can also be used. The present invention can also be realized in the form of a computer data signal embedded in a carrier wave in which the program code is embodied by electronic transmission.

  The present invention is not limited to the above-described embodiments, and various modifications can be made within the scope of the claims, and embodiments obtained by appropriately combining technical means disclosed in different embodiments. Is also included in the technical scope of the present invention.

  The present invention can be applied to a playback apparatus that performs a decoding process (such as an iterative decoding method) using a statistic that represents variations in playback information.

It is a block diagram which shows the structure of the reproducing | regenerating apparatus concerning one Embodiment of this invention. It is a graph which shows an example of the generation frequency of data 0 and data 1 in a reproduction signal. FIG. 2 is a block diagram illustrating a configuration of a data determination circuit provided in the reproduction apparatus illustrated in FIG. 1. It is explanatory drawing which shows the example of the block allocation system of the information recorded on a medium. (A) And (b) is a timing chart of the dispersion | distribution calculation process and decoding process in the reproducing | regenerating apparatus shown in FIG. 3 is a graph showing the result of measuring the bit error rate by changing the SNR in the reproducing apparatus shown in FIG. It is a graph which shows distribution of the data 0 in case of SNR = 10.2dB. 3 is a graph showing a relationship between a threshold value for discriminating two data and a measurement result of a bit error rate in the reproducing apparatus shown in FIG. 3 is a graph showing bit error rates for all combinations of data 1 distribution and data 0 distribution in the reproduction apparatus shown in FIG. 1. It is a block diagram which shows the structure of the reproducing | regenerating apparatus concerning other embodiment of this invention. It is a block diagram which shows the structure of the distributed arithmetic circuit with which the reproducing | regenerating apparatus shown in FIG. 10 is equipped. 11 is a graph showing an example of a relationship between a distribution of a reproduction signal and S0L, S0H, S1L, and S1H in the reproduction apparatus shown in FIG. It is a block diagram which shows the structure of the data discrimination circuit with which the reproducing | regenerating apparatus concerning further another embodiment of this invention is equipped. FIG. 14 is a timing chart showing an example of a start signal generation timing in the playback apparatus of FIG. 13. FIG. FIG. 14 is a timing chart showing another example of Start signal generation timing in the playback apparatus of FIG. 13. FIG. It is a block diagram which shows the structure of the reproducing | regenerating apparatus concerning other embodiment of this invention. FIG. 17 is a graph showing a distribution of signals reproduced by the reproducing apparatus shown in FIG. It is a block diagram which shows the structure of the conventional decoding apparatus. It is a graph which shows the relationship between the standard deviation used for decoding calculation, and a bit error rate in the conventional decoding apparatus.

Explanation of symbols

1. Medium (information recording medium)
2 Reproducing head (reproducing means)
4 Decoding circuit (decoding means)
5 Data discrimination circuit (statistics calculation means, data discrimination means)
5b Data discrimination circuit (statistics calculation means, data discrimination means)
6, 7 Variance calculation circuit (statistics calculation means, calculation means)
8 Distributed arithmetic circuit (statistics calculation means)
9 Differential circuit (statistics calculation means, differential detection means)
10 Absolute value calculation circuit (statistics calculation means, absolute value calculation means)
11 Variance calculation circuit (statistics calculation means, calculation means)
51 Comparison circuit (first comparison means)
52 Temporary Data 1 Average Value Calculation Circuit (Average Value Calculation Means)
53 Temporary data 0 average value calculation circuit (average value calculation means)
54 Comparison circuit (second comparison means)
55 Threshold calculation circuit (threshold calculation means)
56 Selection circuit (selection means)
57 Data generator (data generating means)
81 Probability detection circuit (probability calculation means A, first probability calculation means)
82 Probability detection circuit (probability calculation means B, second probability calculation means)
83 Probability detection circuit (probability calculation means A, third probability calculation means)
84 probability detection circuit (probability detection means B, fourth probability calculation means)
85 σ ₀ calculation circuit (calculation means, first calculation means)
86 σ ₁ calculation circuit (calculation means, second calculation means)
100, 100b, 100d playback device

Claims (12)

A decoding device for decoding an encoded data signal sequence,
A statistic calculating means for calculating a statistic indicating variation of signals included in the data signal sequence based on the data signal sequence;
Decoding means for decoding the data signal sequence using the statistics calculated by the statistics calculation means ,
The above statistic calculation means is:
A plurality of calculating means each for calculating a statistic indicating variation of the input signal;
Data discrimination means for discriminating a signal level of a signal included in the data signal sequence and distributing the signal to any of the plurality of calculation means according to the discriminated signal level;
The data discrimination means is
Data generating means for generating the same signal as the statistic calculation signal included in the data signal sequence;
A decoding device comprising: selection means for determining a signal level of a signal included in the data signal sequence based on a signal generated by the data generation means . A decoding device for decoding an encoded data signal sequence,
A statistic calculating means for calculating a statistic indicating variation of signals included in the data signal sequence based on the data signal sequence;
Decoding means for decoding the data signal sequence using the statistics calculated by the statistics calculation means ,
The above statistic calculation means is:
Probability calculating means A for calculating a probability that the signal level of the signal included in the data signal sequence is equal to or lower than a preset reference value SL;
Probability calculation means B for calculating a probability that the signal level of the signal included in the data signal sequence is equal to or lower than a preset reference value SH;
A decoding apparatus, comprising: a calculation unit that calculates a statistic indicating a variation in a signal included in the data signal sequence based on the probabilities calculated by the probability calculation unit A and the probability calculation unit B. A decoding device for decoding an encoded data signal sequence,
A statistic calculating means for calculating a statistic indicating variation of signals included in the data signal sequence based on the data signal sequence;
Decoding means for decoding the data signal sequence using the statistics calculated by the statistics calculation means ,
The above statistic calculation means is:
First probability calculating means for calculating a probability that a signal belonging to the first signal level among signals included in the data signal sequence is equal to or lower than a first reference value set in advance;
Second probability calculating means for calculating a probability that a signal belonging to the first signal level among signals included in the data signal sequence is equal to or lower than a preset second reference value;
Third probability calculating means for calculating a probability that a signal belonging to the second signal level among signals included in the data signal sequence is equal to or higher than a preset third reference value;
Fourth probability calculating means for calculating a probability that a signal belonging to the second signal level among signals included in the data signal sequence is equal to or higher than a preset fourth reference value;
First calculation means for calculating a statistic indicating variation in signals belonging to the first signal level based on the probabilities calculated by the first probability calculation means and the second probability calculation means;
And second calculation means for calculating a statistic indicating variation in signals belonging to the second signal level based on the probabilities calculated by the third probability calculation means and the fourth probability calculation means. Decoding device. A decoding device for decoding an encoded data signal sequence,
A statistic calculating means for calculating a statistic indicating variation of signals included in the data signal sequence based on the data signal sequence;
Decoding means for decoding the data signal sequence using the statistics calculated by the statistics calculation means ,
The above statistic calculation means is:
Differential detection means for differentially detecting the data signal sequence ;
Absolute value calculating means for calculating the absolute value of the detection result of the differential detecting means;
A decoding apparatus, comprising: a calculating unit that calculates the statistic based on the absolute value calculated by the absolute value calculating unit . Processing for sequentially calculating the statistics of each signal included in the data signal sequence by the statistics calculation means;
Decoding apparatus according to any one of 4 from claim 1, characterized in that parallel processing of a process of sequentially decoding each signal included in the data signal sequence by the decoding means. 6. A reproducing apparatus comprising: reproducing means for reading information recorded on an information recording medium; and the decoding apparatus according to claim 1. A decoding program for operating the decoding device according to any one of claims 1 to 4 , wherein the decoding function causes a computer to function as each of the means. A computer-readable recording medium on which the decoding program according to claim 7 is recorded. A decoding method for decoding an encoded data signal sequence, comprising:
A statistic calculation step of calculating a statistic indicating variation of signals included in the data signal sequence based on the data signal sequence;
A decoding step of decoding the data signal sequence using the statistic calculated in the statistic calculation step,
The above statistic calculation step
The signal level of the signal included in the data signal sequence is determined, and the signal is distributed to any one of a plurality of calculation means for calculating statistics indicating the variation of the input signal according to the determined signal level. Including a data discrimination process to
The data discrimination process
A data generation step for generating the same signal as the statistic calculation signal included in the data signal sequence, and a selection step for determining the signal level of the signal included in the data signal sequence based on the signal generated in the data generation step The decoding method characterized by including . A decoding method for decoding an encoded data signal sequence, comprising:
A statistic calculation step of calculating a statistic indicating variation of signals included in the data signal sequence based on the data signal sequence;
A decoding step of decoding the data signal sequence using the statistic calculated in the statistic calculation step,
The above statistic calculation step
A probability calculating step A for calculating a probability that a signal level of a signal included in the data signal sequence is equal to or lower than a preset reference value SL;
A probability calculating step B for calculating a probability that a signal level of a signal included in the data signal sequence is equal to or lower than a preset reference value SH;
And a calculation step of calculating a statistic indicating variation in signals included in the data signal sequence based on the probabilities calculated in the probability calculation step A and the probability calculation step B. A decoding method for decoding an encoded data signal sequence, comprising:
A statistic calculation step of calculating a statistic indicating variation of signals included in the data signal sequence based on the data signal sequence;
A decoding step of decoding the data signal sequence using the statistic calculated in the statistic calculation step,
The above statistic calculation step
A first probability calculating step of calculating a probability that a signal belonging to the first signal level among signals included in the data signal sequence is equal to or lower than a first reference value set in advance;
A second probability calculating step of calculating a probability that a signal belonging to the first signal level among signals included in the data signal sequence is equal to or lower than a preset second reference value;
A third probability calculating step of calculating a probability that a signal belonging to the second signal level is equal to or higher than a preset third reference value among signals included in the data signal sequence;
A fourth probability calculating step of calculating a probability that a signal belonging to the second signal level among the signals included in the data signal sequence is equal to or higher than a preset fourth reference value;
A first calculation step of calculating a statistic indicating a variation of the signal belonging to the first signal level based on the probabilities calculated in the first probability calculation step and the second probability calculation step;
A decoding method comprising: a second calculation step of calculating a statistic indicating a variation of the signal belonging to the second signal level based on the probabilities calculated in the third probability calculation step and the fourth probability calculation step. . A decoding method for decoding an encoded data signal sequence, comprising:
A statistic calculation step of calculating a statistic indicating variation of signals included in the data signal sequence based on the data signal sequence;
A decoding step of decoding the data signal sequence using the statistic calculated in the statistic calculation step,
The above statistic calculation step
A differential detection step of differentially detecting the data signal sequence ;
An absolute value calculating step of calculating the absolute value of the detection result of the differential detection step;
And a calculating step of calculating the statistic based on the absolute value calculated in the absolute value calculating step .

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