JPH11340834A - Decoding method for digital signal - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide decoding method for a digital signal by which the digital signal is decoded with high precision without causing much increase in arithmetic amount. SOLUTION: Spectrum data formed as units are received, and a maximum absolute value of a scale factor is obtained (S1, S2). Then whether a scale amount is to be fixed or made variable is discriminated by using a threshold, based on the obtained maximum absolute value (S3, S5). Then IMDCT processing is applied to the data based on the result of discrimination (S4, S6, S7), and audio data are outputted (S8). Since scaling method is discriminated depending on the spectrum data, decoding with high accuracy is attained without causing much increase in an arithmetic amount.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for decoding a digital signal for decoding an encoded digital signal, and more particularly to a method for scaling a value to be operated on in an operation for decoding. The present invention relates to a digital signal decoding method.

[0002]

2. Description of the Related Art Conventionally, a digital signal processor (DSP; digital signal processor) adopting a fixed-point display is used.
A block floating technique is known as an encoding technique in the process. In this technique, a digital signal is divided into blocks at predetermined time intervals and at predetermined word counts, and floating processing is performed in block units.

There is also known an encoding technique called orthogonal transform encoding, which performs orthogonal transformation on an input digital signal on a time axis, converts the signal into spectrum data on a frequency axis, and encodes the data. I have.

Further, before performing the orthogonal transform coding,
There is also known a technique of reducing the number of bits of a digital signal to be orthogonally transformed by applying the above-described block floating technique to the digital signal. Such a technique is disclosed, for example, in Japanese Patent Laid-Open No. 4-30254.
No. 0 discloses this.

In the configuration described in this publication, the block length in block floating performed at the time of orthogonal transformation is variable. Then, in this configuration, in order to reduce the amount of calculation for determining the block length, the block length and the block floating coefficient are determined based on the same index of the digital signal, for example, the maximum absolute value of the signal. It has become so.

Japanese Patent Application Laid-Open No. 6-164414 discloses a configuration for reducing a calculation error caused by a decrease in the number of bits of a digital signal. That is,
In this configuration, when an orthogonal transform operation or an inverse orthogonal transform operation is performed on a digital signal, the scale-down is performed. And in this configuration,
The input data value in each of the above calculations is compared with a preset scale-down determination reference value, and the presence or absence of scale-down in each of the calculation processes is determined.

In addition, the inventors of the present application, when judging the scale down, replace the input data of each calculation formula with a representative value of the spectrum data of each unit (for example, a scale factor value in ATRAC speech coding and decoding). It is proposed in Japanese Patent Application No. 9-303002 that the amount of calculation required for determination is reduced and the scale-down width is realized with a finer precision than a simple bit shift.

[0008]

However, in the configuration described in JP-A-6-164414, since the scale-up or scale-down is performed based on the input data sequence in each operation process, the input signal is Although it has a certain effect when the signal has a medium to small amplitude, it consumes much power and is not suitable for a small portable device.

In the configuration described in Japanese Patent Application Laid-Open No. 4-302540, when the input signal has a large amplitude, an operation with the same precision as the configuration described in Japanese Patent Application Laid-Open No. 6-164414 is performed with a smaller amount of calculation. The result can be derived. However, when the input signal has a small amplitude, the calculation accuracy is inferior.

Furthermore, in these conventional configurations, when the input signal is a no signal or a minute signal, the effect of scale-up and scale-down is small. Therefore, it is not possible to expect an improvement in the calculation accuracy just enough to increase the amount of calculation for performing the scale-up or scale-down.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned conventional problems. An object of the present invention is to provide a digital signal decoding method for performing high-accuracy decoding without greatly increasing the amount of computation. To provide.

[0012]

In order to achieve the above object, a digital signal decoding method according to the present invention is divided into a plurality of units by a time range and a frequency domain. In a digital signal decoding method for decoding spectrum data encoded for each unit based on an index value set for each unit, a first method for searching for a representative value from index values in each unit is provided. A second step of determining whether or not to perform scaling on an operand value in an operation for decoding based on the representative value; and an operand value based on a determination result in the second step. And a third step of performing scaling.

In the above method, the spectrum data is a digital signal obtained by sampling, which is a modified discrete cosine transform (MDCT).
It is a digital signal in the frequency space obtained by performing processing or the like. The spectrum data is divided into a plurality of units by a predetermined time range and a predetermined frequency range. Here, the time range is, for example, a time range in which the digital signal is sampled.

A predetermined number of spectrum data belong to each unit, and the spectrum data is encoded for each unit. The quantization for each unit is performed based on the index value in each unit. As the index value, for example, the maximum value of the amplitude values of the spectrum data belonging to each unit is used.

In the above method, when decoding the spectrum data divided into such units,
In order to avoid overflow in the arithmetic processing in the decoding process, or to decode data having a small amplitude with high accuracy, scaling can be applied to the value to be operated. The operated value is an input value in each operation process, that is, data related to the operation.
Note that scaling refers to expanding (scale-up) or reducing (scale-down) the amplitude value of the operated value.

That is, in the first step, a representative value is searched from the index values in each unit.
As the representative value, for example, the maximum value of all index values is used.

Then, in the second step, it is determined whether or not to perform scaling based on the representative value. Then, scaling is performed in a third step based on the determination result of this step.

Thus, according to the above-described method, the calculation error due to the overflow can be avoided by the scaling, and the data having the small amplitude can be decoded with high accuracy. Furthermore, since it is determined whether or not to perform scaling, scaling is not performed on data that does not need to be scaled. Therefore, the amount of calculation in the decoding process can be reduced. Further, since this determination is made based on the representative value of the index value in each unit, the processing amount for this determination is very small. As described above, according to the above method, it is possible to improve the accuracy in decoding a digital signal without increasing the amount of calculation.

In the digital signal according to the second aspect of the present invention, in addition to the method according to the first aspect, a scale amount for scaling in the third step is determined based on the representative value. And a fourth step of performing the above.

According to the above method, all the scale amounts of the arithmetic processing are determined based on the representative values. For this reason, it is possible to determine the scale amount by a very simple process. Therefore, according to this method, the digital signal decoding method described in claim 1 can be easily realized, and the amount of calculation can be further reduced.

According to a third aspect of the present invention, in the digital signal decoding method, in addition to the method of the first aspect, a scale amount for the scaling in the third step is determined by calculating the scale amount in the operation. It is characterized in that it includes a fifth step of determining based on the operated value.

According to the above method, the scale amount in the arithmetic processing is determined based on the operated value which is the input data of each arithmetic processing. For this reason, in each operation process, an optimal scaling can be applied to the value to be operated. Therefore, according to this method, the decoding accuracy of the digital signal can be made very high.

According to a fourth aspect of the present invention, in addition to the method of the first aspect, the digital signal decoding method further comprises the step of:
A sixth step of determining whether to determine based on the representative value or based on a value to be operated on in the calculation, and determining the scale amount based on a result of the determination. I have.

According to the above method, it is determined in the sixth step whether to determine the scale amount based on the representative value or to determine the scale amount in each operation process based on the operated value. It has become. And
This determination is made based on the representative value.

Therefore, according to this method, the method of determining the scale amount is determined according to the spectrum data to be decoded, so that the optimum scaling can be performed according to the characteristics of the spectrum data. I have. Further, since this determination is performed using the representative value, the amount of calculation processing for this determination is very small. Therefore, according to the above-described method, it is possible to perform optimal scaling without increasing the amount of calculation.

According to a fifth aspect of the present invention, there is provided a digital signal decoding method according to any one of the first to fourth aspects, wherein the index value is equal to the spectrum of each unit. In addition to the maximum amplitude value of the data, the representative value is a maximum value in the index values of all units.

According to the above configuration, the representative value becomes the maximum value in the amplitude value of the spectrum data. Therefore, since scaling is performed based on this representative value, it is possible to reliably avoid overflow in arithmetic processing during scaling. Further, according to this method, since the scaling and the maximum value of the index value may be selected to select the index value and the representative value, the selection process can be extremely simplified. As described above, according to the above method, it is possible to reliably avoid an overflow in the arithmetic processing without increasing the amount of arithmetic.

According to a sixth aspect of the present invention, there is provided a digital signal decoding method, wherein the digital signal is divided into a plurality of units by a time range and a frequency domain, and each unit is divided based on an index value set for each unit. 7. A method of decoding a digital signal for decoding spectrum data quantized to: a seventh step of searching for a representative value from index values in each unit; An eighth step of scaling the value, and determining whether the scale amount for the scaling in the eighth step is determined based on the representative value or based on a value to be operated on in the operation. Judge,
A ninth step of determining the scale amount based on the determination result.

According to the above method, when decoding the spectrum data divided into units, in order to avoid an overflow in the arithmetic processing in the decoding process, or to decode minute amplitude data with high accuracy, The operation value is scaled.

That is, first, in the seventh step, a representative value is searched from the index values in each unit.
As the representative value, for example, the maximum value of all index values is used. Then, in the ninth step, it is determined whether to determine the scale amount based on the representative value or whether to determine the scale amount in each calculation process based on the operated value. This determination is made based on the representative value. Then, the scale amount is determined based on the determination result. Then, in the eighth step, the value to be operated is scaled based on the scale amount.

Thus, according to the above-described method, a calculation error due to overflow can be avoided by scaling, and data with a small amplitude can be decoded with high accuracy. Furthermore, since the method of determining the scale amount is determined according to the spectrum data for decoding, optimal scaling can be performed according to the characteristics of the spectrum data. Further, since this determination is made using the representative value, the amount of calculation processing for this determination is very small. As described above, according to the above method, it is possible to decode a digital signal by optimal scaling without increasing the amount of calculation.

According to a seventh aspect of the present invention, there is provided a digital signal decoding method according to the sixth aspect, wherein the index value is a maximum amplitude value of spectrum data in each unit. The representative value is a maximum value of the index values of all units.

According to the above method, the representative value becomes the maximum value in the amplitude value of the spectrum data. Therefore, since scaling is performed based on this representative value, it is possible to reliably avoid overflow in arithmetic processing during scaling. Further, according to this method, since the scaling and the maximum value of the index value may be selected to select the index value and the representative value, the selection process can be extremely simplified. As described above, according to the above method, it is possible to reliably avoid an overflow in the arithmetic processing without increasing the amount of arithmetic.

[0034]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS [First Embodiment] A first embodiment of the present invention will be described below. FIG. 2 is an explanatory diagram showing a configuration of a mini disc recording / reproducing apparatus 1 which is a digital recording / reproducing apparatus according to the present embodiment. As shown in FIG. 1, the mini disc recording / reproducing apparatus 1 includes an input terminal 2, an optical element 3, a digital PLL circuit 4, a frequency conversion circuit 5, an audio compression circuit 6, an audio expansion circuit 9, a shock proof memory controller 7, a shock proof memory Proof memory 8, signal processing circuit 10, head drive circuit 11, recording head 12, optical pickup 13, spindle motor 14,
Feed motor 15, driver circuit 16, servo circuit 17,
RF amplifier 18, D / A converter 19, output terminal 20, system control microcomputer 22, and power supply ON / OF
An F circuit 23 is provided. Further, the magneto-optical disk 25 in this figure is a mini-disc which can be recorded and reproduced by the mini-disc recording and reproducing apparatus 1.

First, the components of the mini disc recording / reproducing apparatus 1 will be described. The photoelectric element 3 converts a digital signal of an optical signal input to the input terminal 2 into a digital signal of an electric signal. Digital PLL circuit 4
Extracts a clock from the digital signal output from the photoelectric element 3 and applies a 48 kHz
The sampling is performed at frequencies of z, 44.1 kHz and 32 kHz, and a signal corresponding to the number of quantization bits is generated and output. Hereinafter, the digital signal generated by the digital PLL circuit 4 is referred to as audio data.

The frequency conversion circuit 5 converts the sampling frequency of the audio data generated by the digital PLL circuit 4 to 44.1 kHz corresponding to the mini disc standard. The audio compression circuit 6 converts the audio data frequency-converted by the frequency conversion circuit 5 into A
The data is subjected to compression coding according to the TRAC (Adaptive TRansform Acoustic Coding) method and is output as audio data (coded audio data). The configuration and operation of the audio compression circuit 6 will be described later.

The shock proof memory 8 is a memory for shock proof processing. The shockproof memory controller 7 uses the shockproof memory 8 to absorb the difference between the speed at which the sound compression circuit 6 outputs sound data and the processing speed of the signal processing circuit 10. Further, the shock proof memory controller 7 uses the shock proof memory 8 to interrupt the digital signal input to the input terminal 2 due to disturbance such as vibration during reproduction, and to input the sound input to the signal processing circuit 10. Interpolates data to protect digital signals or audio data. Such processing by the shock proof memory controller 7 and the shock proof memory 8 is called shock proof processing.

The signal processing circuit 10 has functions as an encoder and a decoder. That is, the signal processing circuit 10 inputs the audio data output from the shockproof memory 8 when recording a digital signal,
The audio data is subjected to an encoding process such as addition of a parity, and the audio data is modulated into a magnetic modulation signal recordable on the magneto-optical disk 25 and output to the head drive circuit 11. When reproducing a digital signal, the signal processing circuit 10 decodes the audio data reproduced from the magneto-optical disk 25 and outputs the decoded data to the audio decompression circuit 9 via the shockproof memory controller 7. .

The audio decompression circuit 9 performs the ATRAC decoding on the audio data output from the signal processing circuit 10. The decoded audio data, that is, audio data, is supplied to the D / A converter 19.
Is converted into an analog audio signal and output from the output terminal 20. The configuration and operation of the audio decompression circuit 9 will be described later.

The head drive circuit 11 moves the recording head 12 to a predetermined recording position on the magneto-optical disk 25, and generates a magnetic field corresponding to the magnetic modulation signal output from the signal processing circuit 10 from the recording head 12. Things.

The optical pickup 13 irradiates a predetermined recording position of the magneto-optical disk 25 with a laser beam during recording and reproduction. At the time of reproduction, the reflected light of the laser light from the magneto-optical disk 25 is read, and the RF signal (modulated audio data) recorded on the magneto-optical disk 25 is detected. The RF amplifier 18 amplifies the RF signal detected by the optical pickup 13. The spindle motor 14 is a magneto-optical disk 2
5 is rotated in a predetermined direction. Feed motor 1
Numeral 5 is for moving the optical pickup 13 in a direction orthogonal to the tracks on the magneto-optical disk 25.

The driver circuit 16 includes a magneto-optical disk 25
Power is supplied to a feed motor 15, a spindle motor 14, and a drive unit (not shown) for driving an objective lens (not shown) of the optical pickup 13 so that a predetermined recording position is irradiated with laser light. Servo circuit 1
7 is based on the output of the RF amplifier 18 so that the operation for recording / reproduction such as making the laser beam emitted from the optical pickup 13 follow the target track of the magneto-optical disk 25 is performed accurately. Each device driven by the driver circuit 16 is feedback-controlled.

The power ON / OFF circuit 23 supplies power to the signal processing circuit 10, optical pickup 13, driver circuit 16, servo circuit 17, RF amplifier 18, system control microcomputer 22, and the like.
The system control microcomputer 22 has a power ON / OF
It is for managing the power ON / OFF operation of the F circuit 23 and centrally managing the signal processing operation by each of the above-described members, and is a central part in the mini disc recording / reproducing apparatus 1.

As described above, the audio compression circuit 6 and the audio decompression circuit 9 encode and decode data by the ATRAC method.
This is a DSP in the mini disc recording / reproducing apparatus 1 for decoding. The ATRAC method is a method used in minidiscs as a method for compressing and encoding digital signals such as musical sounds and voices with high efficiency. In this method, a digital signal sampled at 44.1 kHz is divided into a predetermined frequency band (low band of 0 to 5.5 kHz, middle band of 5.5 to 11 kHz, and high band of 11 to 22 kHz). Are divided into variable length unit times for each frequency band. Then, the blocked digital signal is converted into a modified discrete cosine (MDCT).
The transform is encoded for each predetermined frequency region. This encoding is performed based on the number of bits assigned using the psychoacoustic characteristics.

Next, the audio compression circuit 6 will be described.
FIG. 3 is an explanatory diagram showing the configuration of the audio compression circuit 6. As shown in this figure, the audio compression circuit 6 includes a band division filter unit 31, a time window cutout unit 32, an MDCT unit 33, a bit allocation unit 34, a unit division unit 35, and a quantization unit 3.
6 and an encoding unit 37.

First, the components of the audio compression circuit 6 will be described. The band division filter unit 31 is a QMF (quadratutu
re-mirror filter), and the audio data input from the frequency conversion circuit 5 is divided into high-frequency signals and low-frequency signals.
It is divided into two frequency bands. The time window cutout unit 32 divides the input audio data into predetermined unit times (11.6 milliseconds, 512 samples).

In the following, the audio data divided by the unit of time by the time window cutout unit 32 will be referred to as grouped audio data. The audio data divided into unit times and divided for each frequency band by the band division filter unit 31 is set as audio data which is divided into blocks. That is, the audio data that is blocked is divided into groups on the time axis,
The audio data is divided into blocks on the time axis and the frequency axis.

The MDCT unit 33 converts the block-structured audio data into MDCT (modifi
ed discrete cosine transform). Since the MDCT process is performed on the audio data for each block by the MDCT unit 33, the spectrum data generated after the process is also divided into blocks.

The bit allocating section 34 allocates the number of quantization bits, that is, the word length (WL) to the divided spectrum data generated by the MDCT section 33 using the psychoacoustic characteristics. The unit dividing unit 35 divides the divided spectrum data generated by the MDCT unit 33 into units divided by a plurality of frequency domains and time ranges. Hereinafter, the spectrum data divided into units will be referred to as unitized spectrum data. Then, the maximum amplitude value in the spectrum data of each unit is obtained as an index value of each unit. Then, this index value is set as a scale factor (SF) of each unit.

The quantization unit 36 quantizes the unitized spectrum data for each unit based on the word length and the scale factor of each unit calculated by the bit allocation unit 34 and the unit division unit 35. .

The encoding section 37 has a predetermined format of 424 bytes (2 × 2 bytes) for each group so that the spectrum data quantized by the quantization section 36 can be recorded on the magneto-optical disk 25 shown in FIG. 212 bytes; 1
(Sound group) to generate audio data in a predetermined compression format. The audio data is quantized and compressed (encoded) spectrum data. The compression format of the audio data will be described later.

Next, the operation of compressing audio data by the audio compression circuit 6 will be described. Frequency conversion circuit 5
(See FIG. 2), the sampling frequency 4
When the 4.1 kHz audio data is input to the audio compression circuit 6, the audio data is divided by the band division filter unit 31 into two blocks of a high band side and a low band side. And
The audio data of the low-frequency side block is again input to the band division filter unit 31, and the frequency band is divided into two. As a result, the audio data input to the audio compression circuit 6 is divided by the band division filter unit 31 into three frequency bands of a high band, a middle band, and a low band.

The audio data divided into three bands by the band division filter unit 31 is divided by the time window cutout unit 32 by a time window of 11.6 ms (512 samples) at the maximum. Therefore, the audio data is 5
It can be said that they are grouped by a time window of 12 samples and are divided into three frequency bands in the group. As described above, the audio data is divided into the time window of 512 samples and the three frequency bands, and becomes the audio data which is divided into blocks.

After that, the block-structured audio data is subjected to MDCT by the MDCT unit 33 for each block.
Processing is performed, and the data is converted into block-spectrum data. Then, after the bit allocation and the calculation of the word length are performed by the bit allocation unit 34 on the divided spectrum data, the unit division unit 35 generates the unitized spectrum data, The scale factor in the unit is set.

FIG. 4 is an explanatory diagram showing an example of unitized spectrum data corresponding to one group of audio data, using a time axis and a frequency axis. As shown in this diagram, the low-frequency block is divided into four equal parts on the time axis and five equal parts on the frequency axis, so that 20 units (Unit in FIG. 4) are obtained.
0 to Unit 19). Each unit in the low-frequency block includes eight pieces of spectrum data (for example, the AS in Unit 0 in FIG. 4).

[0] to AS [7]).

The block in the middle band is divided into four equal parts on the time axis and four equal parts on the frequency axis, thereby forming 16 units (Unit in FIG. 4).
20 to Unit 35). Each unit in the middle range block has six pieces of spectrum data (for example, AS [1 in Unit 20 in FIG. 4).
28] to AS [133]).

The high-frequency block is divided into eight equal parts on the time axis and two equal parts on the frequency axis to obtain 16 units (Unit in FIG. 4).
36 to Unit 51). Each unit in the high-frequency block includes 12 pieces of spectrum data (for example, the AS in Unit 36 in FIG. 4).
[256] to AS [267]). Thus, in this example, 512 (AS

[0] to AS [51
1)) of 52 spectrum data (Unit0 to Unit0)
(Unit 51). Further, the number of spectrum data included in each unit is different for each of the three blocks. It should be noted that the blocks and units shown in FIG. 4 are merely examples, and the present invention is not limited thereto.

After being unitized by the unit dividing section 35 as described above, the spectrum data is quantized by the quantizing section 36 based on the word length and the scale factor. The quantized spectrum data is encoded by the encoding unit 37 into 424 bytes (2 × 212 bytes;
(1 sound group).

FIG. 5 is an explanatory diagram showing the format of the audio data. FIG. 5 shows one channel (212 bytes) of 424 bytes.
As shown in this figure, in this format, BSM, SIA of main data, index of word length and index of scale factor, quantized spectrum data, and BSM, SIA of sub data, index and scale of word length. A factor index is recorded. The content of the information of the sub data is almost the same as the information of the main data.

The BSM (block size mode) is information on blocking and unitization of spectrum data. Also, SIA (sub information amount)
Is information on the number of units in each block of the spectrum data. Word length index (WLI)
Is a word length (W) which is the number of quantization bits of each unit.
L) is an index. Table 1 shows the correspondence between the WLI and the word length (WL). As shown in this table, the word length (WL) is an integer from 0 to 16 excluding 1, and WLIs from 0 to 15 correspond in ascending order.

[0061]

[Table 1]

The scale factor index (SF
I) is an index of a scale factor (SF), which is the magnitude of the amplitude of the representative spectrum data of each unit. Table 2 shows the correspondence between these SFIs and scale factors (SF). As shown in this table, the scale factor (SF) is a number expressed in the form of a product of a coefficient m [i] and 2 ⁿ . Where i and n are 1
≦ i ≦ 3, −5 ≦ n ≦ 16. Also, m
[I] is m [1] = 0.62996052, m [2] = 0.793700
52, m [3] = 0.999999999. Also, n = −5 and m
The product of [1] and m [2] is excluded from the scale factor.

The scale factors correspond to SFIs from 0 to 63 in ascending order. That is,
The scale factor has 64 stages. Also, three coefficients m [1], m [2], m [3] for one n
, One bit corresponds to three SFIs.

[0064]

[Table 2]

The scale factor in the block is
Up to 5 because it exists for each unit included in each block
There are two. On the other hand, there are 512 quantized spectrum data at maximum because there are as many as the number of sampled audio data. The unit includes at least one piece of quantized spectrum data. Thus, it is clear that the number of scale factors in a block is smaller than the number of quantized spectrum data.

Next, the audio decompression circuit 9 shown in FIG. 2 will be described. FIG. 6 is an explanatory diagram showing the configuration of the audio decompression circuit 9. As shown in FIG.
Are the storage unit 40, the WL development unit 41, the SF development unit 42,
An S expansion unit 43, an SF maximum value determination unit 44, an SF offset attaching unit 45, an inverse quantization unit 46, an IMDCT unit 47, an inverse floating unit 48, a windowing unit 49, and a band synthesis filter unit 50 are provided.

The WL expanding section 41 expands the word length of each unit in the three blocks into a numerical value of the actual word length according to Table 1 based on the WLI in the audio data of the format shown in FIG. Is what you do. Similarly, the SF expanding unit 42 expands the scale factor of each unit in the block according to Table 2 based on the SFI.

The AS expanding section 43 expands the spectrum data compressed over several words for each word. That is, the AS expanding section 43 reads out the quantized spectrum data stored in various states by 8 bits, and expands the data for each word.

Since the maximum value of the word length is 16 bits, when one word can be read by one reading,
When data can be read by two readings, data can be read by three readings. That is, the content of the processing performed by the AS expanding section 43 is to read out the quantized spectrum data stored in various states by 8 bits at a time, and to cut it at every word (up to 16 bits).

The maximum SF value determining section 44 searches for a unit having the largest scale factor in each block, and obtains the scale factor of this unit as a representative value of the block. The SF offset attaching unit 45 updates the SFI of each unit for each block so that the maximum value of the scale factor acquired by the SF maximum value determining unit 44 is m [3] × 2 ¹⁶ (SFI = 63). Is what you do. That is, the SF offset attaching section 45
Is the SF according to the maximum scale factor of each block
I is subtracted from 63 and set as an SFI offset value (scale amount). Then, the SF offset assigning unit 45 updates these SFIs by adding the obtained offset values to the SFIs of all units in the block. Note that this offset value is equal to the SFI
Is determined so that the update of the process does not cause an overflow in the process of the IMDCT unit 47 described later.

The inverse quantization unit 46 performs an inverse quantization of the spectrum data in the audio data based on the word length obtained by the WL expansion unit 41 and the scale factor indicated by the SFI updated by the SF offset attaching unit 45. Is what you do. This inverse quantization will be described later.

The IMDCT unit 47 performs an IMDCT on the spectrum data dequantized by the dequantization unit 46.
(Invers modified discrete cosine transform) processing is performed to generate blocked audio data. The detailed configuration and processing of the IMDCT unit 47 will be described later.

The inverse floating unit 48 appropriately corrects and outputs the amplitude value of the block audio data generated by the IMDCT unit 47. That is, in the IMDCT processing in the IMDCT section 47, scaling is performed on the spectrum data in order to prevent overflow of the arithmetic processing. Therefore, the inverse floating unit 48 corrects the amplitude value converted by the scaling to an appropriate value. Note that scaling refers to the IMDCT unit 4
7, scale-down and scale-up performed on data (operated value) related to the operation in the IMDCT process.

The window portion 49 is provided with an inverted floating portion 48.
Audio data output from
They are connected on the time axis. That is, the window portion 49
Performs windowing processing on certain data and data one sample before on the time axis.

The band synthesis filter section 50 has an IQMF (In
A band synthesis filter such as a vers quadrature mirror filter) is provided to combine audio data divided into three for each frequency band into one. That is, the band synthesizing filter unit 50 synthesizes the blocked audio data and outputs it to the D / A converter 19 shown in FIG. The storage unit 40 stores the above-described audio decompression circuit 9
Are for storing information necessary for each process.

Next, the operation of expanding the audio data by the audio expansion circuit 9 will be described. In addition, (2)-which will be described later
IMDCT processing using equation (6) is described in IEICE Technical Report, CAS90-
9 DSP90-13, "A Study on MDCT Method and High-speed Algorithm", Masahiro Iwatari, Takao Nishitani, Akihiko Sugiyama, et al.
EEE, Transactions on ASSP, Vol. 34, No. 5, "Analysis / Synthesis Filter Bank Design Based on Alias Cancellation in the Time Domain", John P. Princen, Alan Bernard Br
It is described in detail in adley.

When audio data in the format shown in FIG. 5 is input from the signal processing circuit 10 to the audio decompression circuit 9 via the shock proof memory controller 7 shown in FIG. Based on this, the word length of each unit in the three blocks of the group corresponding to the audio data is developed and stored in the storage unit 40. Similarly, the SF expanding unit 42 expands the scale factor of each unit based on the SFI, and causes the storage unit 40 to store the scale factor.

After that, the AS expanding section 43 reads out the quantized spectrum data in the audio data in units of 8 bits and expands it for each word. Then, the SF maximum value determination unit 44 searches for the unit having the maximum scale factor for each block, and acquires the maximum value of the scale factor in each block. Then, the SF offset assigning unit 45 calculates the SFI offset value (scale amount) such that the maximum value of the scale factor in each block is m [3] × 2 ¹⁶ (SFI = 63).

Then, the SF offset attaching section 45 updates the SFI of each unit by adding this offset value to the SFI of all units belonging to each block. Further, the SF offset attaching section 45 calculates the calculated offset value, the updated SFI, and the SF
The storage unit 40 stores the scale factor corresponding to I.

After the SFI of each block is updated, the inverse quantization unit 46 determines the word length expanded by the WL expansion unit 41,
The scale factor according to the SFI updated by the SF offset attaching unit 45 is acquired from the storage unit 40. Then, using these values and the following equation (1), an inverse quantization process is performed on the quantized spectrum data expanded by the AS expansion unit 43 for each unit. This allows
The quantized spectrum data AS [j] is inversely quantized to generate unitized spectrum data X [k].

[0081]

(Equation 1)

In this equation, WL [i] indicates the word length of each unit, i indicates the unit number, j indicates the quantized spectrum data number, and k indicates the spectrum data number. Also, 0 ≦ i ≦ N, 0 ≦
j, k ≦ M−1. N indicates the maximum value of the unit number, and M-1 indicates the maximum value of the spectrum data number. Also, N <M-1.

After that, the IMDCT unit 47 applies the I / O to the unitized spectrum data for each block.
An MDCT process is performed to generate audio data blocked into three frequency bands of a high band, a middle band, and a low band, and output to the inverse floating unit 48. In addition, IMD
The detailed configuration and operation of the CT unit 47 will be described later.

Thereafter, the inverse floating unit 48 sets the IMDCT unit 4 on the basis of a predetermined SFI (for example, 63).
7 corrects the amplitude value of the block-structured audio data output to the windowing unit 49 and ends the reverse floating. The operation of the reverse floating section 48 will be described later.

Thereafter, the windowing section 49 performs windowing processing on the block-structured audio data output from the inverse floating section 48, adjusts between adjacent frames on the time axis, and performs a band synthesis filter. Output to the unit 50. Then, the band synthesis filter unit 50 generates one group of audio data, and the decoding process by the audio decompression circuit 9 ends.

Next, the configuration and operation of the IMDCT unit 47 will be described. FIG. 7 is an explanatory diagram showing the configuration of the IMDCT unit 47. As shown in this figure, the IMDCT unit 47 includes a U (k) calculation unit 51, an FFT calculation unit 52,
(N) calculation unit 53, y (n) calculation unit 54, fixed scaling unit 55, fixed scale amount loading unit 56, and fixed scale amount memory 57.

As described above, the IMDCT unit 47 applies the IMDCT to the unitized spectrum data.
T processing is performed. That is, the U (k) calculation unit 5
The 1-y (n) calculation unit 54 performs the arithmetic processing shown in the following (2) to (6) on the unitized spectrum data.

The fixed scaling unit 55, fixed scale amount loading unit 56 and fixed scale amount memory 57
Before the arithmetic processing shown in equations (3) to (5) is performed, in order to prevent overflow in the course of the arithmetic,
A predetermined scaling is performed on the operand value.

The operation of the IMDCT unit 47 will be described below. When the unitized spectrum data is input to the IMDCT unit 47, the U (k) calculation unit 51
U (k) corresponding to the spectrum data X [k] input to the IMDCT unit 47 is calculated using the following equation (2), and is output to the fixed scaling unit 55. The fixed scaling unit 55 performs predetermined scaling described later on the U (k), and outputs the result to the U (k) calculation unit 51.

Thereafter, the U (k) calculating section 51 derives Z (L) for each U (k) using the following equation (3), and outputs it to the fixed scaling section 55 again. Note that Re [Z (L)] and Im [Z (L)] in this equation are:
The real part and the imaginary part of the complex number Z [L] are shown. L is
0 ≦ L <M / 2.

[0091]

(Equation 2)

[0092]

(Equation 3)

The fixed scaling unit 55 receives the input Z
(L) is subjected to predetermined scaling described later, and F
It is input to the FT calculation unit 52. The FFT calculation unit 52 performs a fast Fourier transform on each of the inputted Z (L) using the following equation (4). That is, the FFT calculation unit 52
Is provided with an FFT first-stage calculation unit to an FFTP-stage calculation unit assuming that P = log ₂ (M / 2), and calculates z (n) by performing a fast Fourier transform by a P-stage butterfly operation.
In the expression (4), i is an imaginary unit. Also, n
Is a number satisfying 0 ≦ n <M / 2.

In this calculation, each FFTp stage calculation unit (p
= 1 to an integer of P), the calculated result is output to the fixed scaling unit 55. Then, fixed scaling section 55 performs predetermined scaling on the input calculation result, and outputs the result to the next-stage FFT (p +
1) Output to the stage calculation unit. And
After the end of the P-stage butterfly operation, the FFT calculation unit 52
z (n) is output to the fixed scaling unit 55.

[0095]

(Equation 4)

The fixed scaling unit 55 receives the input z
(N) is subjected to predetermined scaling described later,
Output to the u (n) calculation unit 53. u (n) calculation unit 53
Calculates u (n) based on the input z (n) using the following equation (5), and outputs it to the y (n) calculating unit 54. Thereafter, the y (n) calculation unit 54 outputs the input u
Based on (n), IMDCT is performed using the following equation (6).
Performs processing and blocks audio data y
(N) is calculated.

[0097]

(Equation 5)

[0098]

(Equation 6)

Here, the above-mentioned fixed scaling unit 55
Will be described. The fixed scale amount memory 57 of the IMDCT unit 47 stores U (k) and each F
A fixed scale amount is stored for an input value (including Z (L)), z (n), and the like on which an operation is preferably performed for scaling, such as an input value to the FTp stage calculation unit.

Then, the fixed scaling unit 55 controls the fixed scale amount loading unit 56 to calculate the fixed scale amount according to the type of each operation based on the maximum scale factor of each block. It is read from the fixed scale amount memory 57. Then, based on the read fixed scale amount, the calculated value is sequentially scaled.

Table 3 shows the fixed scale amounts stored in the fixed scale amount memory 57. As shown in this table, these fixed scale amounts are calculated by
Scale factor (S
F) according to the maximum value.

In this table, the fixed scale amount is represented by the number of bits. That is, the positive integer in this table is
This is a scale amount for performing scaling for bit shifting the operand value to the LSB (Least Significant Bit) side (hereinafter, referred to as right side). Further, the negative integer is a scale amount for performing scaling for bit-shifting the operand value to the MSB (Most Significant Bit) side (hereinafter, referred to as a left side). In this table, the input values to the FFT calculation unit are shown up to the fourth stage. Also, in this table,
The maximum value of the scale factor value at 2 ^{8-2 -4} is omitted, this is fixed scale of the maximum value of the scale factor 2 ⁹ or less is because all the same value.

[0103]

[Table 3]

The fixed scale amount as shown in this table is:
It is determined as follows. That is, (3) to above
The calculation result obtained by the calculation processing shown in equation (5) is different in magnitude from the value to be operated. Table 4 shows the ratio of the operation result to the operated value for each operation process. In the upper bits of the operand value of the operation result, margin bits as shown in Table 4 are generated according to the ratio (or magnification) of the operand value before and after the operation. This margin bit is transmitted to the IMDCT unit 4
7 is determined by the design. Table 5 shows the ratio of the operated value to the operation result for each operation process. The methods for obtaining the magnifications and ratios shown in Tables 4 and 5 are described in detail in JP-A-7-36666.

[0105]

[Table 4]

[0106]

[Table 5]

Therefore, the operation result becomes too large and I
It can be seen that the fixed scale amount is preferably set so that the processing in any configuration in the MDCT unit 47 does not overflow. The fixed scale amount is determined based on the following conditions (1) to (4).

The amplitude value in the spectrum data input to the IMDCT unit 47 is 2 ¹⁶ at the maximum. The maximum amplitude value of the audio data output from the IMDCT unit 47 is 2 ¹⁵ . According to the above and the magnifications and ratios shown in Tables 4 and 5, some of the calculation results in each configuration of the IMDCT unit 47 have a maximum value.

When the maximum value of the operation result in each component of the IMDCT unit 47 is represented by a power of 2, if the envelope representing each maximum value is obtained, the fixed scale amount shown in Table 3 can be obtained. it can. The method of obtaining the fixed scale amount is described in detail in the above-mentioned Japanese Patent Application Laid-Open No. 7-36666.

Next, the operation of the reverse floating section 48 will be described. As described above, the reverse floating portion 4
8 corrects the amplitude value of the audio data output from the IMDCT unit 47. That is, the inverse floating unit 48 obtains the sum of the fixed scale amounts used for the scaling performed on the operand value before the processing of the above-described equations (3) to (5), and calculates the sum thus obtained. The tripled value is subtracted from the SFI offset value of each unit before the processing in the IMDCT unit 47, and a new offset value is obtained.

Then, based on the offset value, the amplitude value of the audio data is corrected using a predetermined SFI as a reference value. That is, the reverse floating unit 48 subtracts the obtained offset value from the reference value to make a new offset value. Then, the scale factor according to the offset value is set as a scale amount, and the amplitude value of the audio data input from the IMDCT unit 47 is multiplied. Thus, the reverse floating process by the reverse floating unit 48 ends. The inverse floating process is a process in which the IMDCT process is performed, and the audio data output from the IMDCT unit 47 is multiplied by a scale factor corresponding to a predetermined offset value.

Here, the reverse floating portion 48 is
The reason why a value obtained by triple the sum of the fixed scale amounts when updating I will be described. The scale factor of the spectrum data is set at intervals obtained by equally dividing 1 dB. That is, a unit of 1 bit corresponds to 3 ranges in SFI (1 bit = 3 indexes). Therefore,
In order to return the SFI offset value, the reverse floating unit 48 subtracts a value obtained by multiplying the total number of bits of the fixed scale amount by three from the offset value.

The following describes an example of processing of the audio decompression circuit 9 after the maximum value of the scale factor is obtained by the SF maximum value determination unit 44. The maximum value of the scale factor of all units in a certain block of audio data to be decoded is m [1] × 2 ¹⁰ = 0.62996052 × 2 ¹⁰ (SFI = 4
Suppose that 3). The SF offset attaching section 45 determines that this value is SFI = 63 (m [3] × 2 ¹⁶ = 0.99999999 × 2
¹⁶ ) Calculate the offset value (scale amount) so that. That is, the offset value in this case is 63-4
3 = 20.

For example, in this block, the scale factor is m [2] × 2 ⁶ = 0.79370052 × 2 ⁶ (S
Assume that there is a unit of which FI = 32). The SF offset adding section 45 adds the above-described scale amount as an offset value to the SFI of this unit, and updates the SFI. That is, the updated SFI is 32 + 20 = 52
(SF = m [1] × 2 ¹³ = 0.62996052 × 2 ¹³ ).
As described above, the SF offset attaching unit 45 updates the SFI in all units in the block.

Thereafter, the inverse quantization by the inverse quantization unit 46 allows the spectrum data X to be obtained from the above equation (1).
After [k] is generated, the IMDCT unit 47 determines that the maximum value of the scale factor in this block is SF = m [1] ×
Since it is 2 ¹⁰ , the fixed scale amount in each arithmetic processing is read by referring to the column of the maximum value of the scale factor 2 ¹⁰ in Table 3. Then, before the operation processing, the operation value is scaled, and then each operation of the IMDCT processing is performed.

That is, before the arithmetic processing in the U (k) calculating section 51 shown in the equation (3), the operated value is shifted to the right by one.
Shift by bits. Then, F shown in equation (4)
Before the processing in the FT first stage calculation unit 52 to the FFT third stage calculation unit, the operand values are each shifted to the right by one bit. Then, before the processing in the FFT fourth stage calculation unit, the operand value is shifted to the right by two bits. Then, before the processing in the u (n) calculation unit 53 shown in the equation (5), no bit shift is performed.

Thereafter, when blocked audio data is generated and input to the inverse floating unit 48, the inverse floating unit 48
The sum of the fixed scale amounts at 7 is determined. That is,
The maximum value of the scale factor in this block is m [1]
× Since was 2 ^10, the maximum value of the scale factor in Table 3 refers to the column of 2 ^10, the total sum reads the fixed scale amount in the IMDCT unit 47, the value determined 3
Multiply by the offset to obtain the SFI offset value.

From this table, the sum of the fixed scale amounts is 1
+ 1 + 1 + 1 + 2 = 6, and the SFI offset value is 18. Also, since the offset value given from the SF offset attaching unit 45 is 20, the offset value is updated to 20− (6 × 3) = 2. Further, the reverse floating unit 48 uses SFI = 15 as a reference value,
Update the offset value. That is, 15-2 = 13. Thereafter, inverse floating unit 48 multiplies a scale factor m [1] × 2 ⁰ indicated by this offset value and the amplitude value of the audio data blocks.
The multiplication may be performed at a fixed point.

As described above, the IMDCT unit 4 in the audio decompression circuit 9 provided in the mini disc recording / reproducing apparatus 1
7, in the block divided for each frequency band,
Based on the maximum value of the scale factor of each unit, I
The value to be operated is scaled so that overflow does not occur in the course of each operation in the MDCT process. As a result, it is possible to reliably remove the calculation error caused by the overflow.

Further, the IMDCT unit 47 searches for a scale factor whose number is smaller than that of the spectrum data in order to obtain the fixed scale amount. Therefore, it is possible to greatly reduce the amount of calculation for obtaining the fixed scale amount. Further, since the scale factor is an absolute value, the amount of calculation can be further reduced. As a result, it is possible to reduce power consumption for arithmetic processing.

Further, in the mini disc recording / reproducing apparatus 1,
The scale factor of the spectrum data is 1 dB to 3
They are set at equally spaced intervals. Therefore, scaling by the IMDCT unit 47 can be performed in units more detailed than one bit. Therefore, it is possible to increase the accuracy of the arithmetic processing as compared with a configuration in which scaling is performed in units of bits.

In this embodiment, the IMDCT unit 4
7, the fixed scale amount stored in the fixed scale amount memory 57 is a value shown in Table 3. However, the fixed scale amount stored in the fixed scale amount memory 57 is not limited to the one in this table. The fixed scale amount may be set so that overflow does not occur in the calculation processing of the U (k) calculation unit 51 to the y (n) calculation unit 54 in the IMDCT unit 47.

The scaling by the IMDCT unit 47 and the inverse quantization by the inverse quantization unit 46 may be performed simultaneously. In the mini-disc recording / reproducing apparatus 1, the above processing is performed using the scale factor, so that such a configuration is possible. With this configuration, the amount of calculation can be further reduced, and the power consumption can be further reduced.

In the present embodiment, the scale factor (index value) of each unit is the maximum amplitude value of the spectrum data in each unit, and the representative value of each block is the maximum value of the scale factor. . However, the method of selecting the index value and the representative value is not limited to this, and may be selected by a method desired by the user. Further, as a reference value of the SFI used by the reverse floating unit 48, a value desired by the user can be used.

In the present embodiment, the audio compression circuit 6 and the audio expansion circuit 9 in the mini disc recording / reproducing apparatus 1 perform ATRAC signal processing. However, the present invention is not limited to this, and an audio compression / expansion circuit provided with an ATRAC processing circuit may be provided instead of the audio compression circuit 6 and the audio expansion circuit 9. Then, all the processing of the audio compression circuit 6 and the audio expansion circuit 9 may be performed by the ATRAC processing circuit in the audio compression / expansion circuit.

In the audio decompression circuit 9 of this embodiment,
Although a predetermined scaling is performed in each process, a configuration in which no scaling is performed may be adopted. FIG. 10 is an explanatory diagram showing the configuration of the audio decompression circuit in a configuration in which scaling is not performed. This configuration includes the SF maximum value determining unit 44 and the SF offset attaching unit 4 shown in FIG.
5, an IMDCT unit 81 is provided in place of the IMDCT unit 47 and the reverse floating unit 48.

FIG. 11 is an explanatory diagram showing the configuration of the IMDCT unit 81. As shown in this figure, the IMDCT unit 81 has a configuration in which the fixed scaling unit 55, the fixed scale amount loading unit 56, and the fixed scale amount memory 57 are not provided in the configuration of the IMDCT unit 47 shown in FIG.

The IMDCT unit 81 is the same as the IMDCT unit 47 except that scaling is not performed. Further, the audio decompression circuit including the IMDCT unit 81 is the same as the audio decompression circuit 9 except that no scaling is performed. That is, when it is not necessary to perform scaling, it is also possible to use an audio decompression circuit having such a configuration.

[Embodiment 2] A second embodiment of the present invention will be described below. The first embodiment described above
Members having the same functions as the members shown in (1) are denoted by the same reference numerals, and description thereof will be omitted.

The digital recording / reproducing apparatus according to the present embodiment has the same structure as the mini-disc recording / reproducing apparatus 1 of the first embodiment except that the I / O
The configuration includes an IMDCT unit 61 instead of the MDCT unit 47.

FIG. 8 is an explanatory diagram showing the configuration of the IMDCT unit 61. As shown in this figure, the IMDCT unit 6
In the configuration of the IMDCT unit 47 shown in the first embodiment, the variable scaling unit 62, the variable scale amount determining unit 63, and the variable scaling unit 62 replace the fixed scaling unit 55, the fixed scale amount loading unit 56, and the fixed scale amount memory 57. This is a configuration including a variable scale memory 64.

The IMDCT unit 61 performs an IMDCT process for each block on the spectrum data input from the inverse quantization unit 46, similarly to the IMDCT unit 47. That is, U in the IMDCT unit 61
(K) The calculation units 51 to y (n) calculation unit 54 perform the above-described calculation processes (2) to (6) on the input spectrum data.

The variable scaling section 62, variable scale amount determination section 63 and variable scale amount memory 64
Is to perform a predetermined scaling on a value to be operated in order to prevent an overflow in the course of the operation before the operation shown in the equations (3) to (5) is performed.

The scaling of the variable value by the variable scaling section 62 will be described below. Like the fixed scaling unit 55, the variable scaling unit 62 once inputs the value to be operated before the arithmetic processing shown in the equations (3) to (5) is performed. Then, the variable scaling unit 62 controls the variable scale amount determination unit 63 to determine the scale amount (variable scale amount) according to the input operated value as follows.

That is, the variable scale amount determination section 63
First, the maximum absolute value of the operand value input to the variable scaling unit 62 is obtained. And the variable scale amount memory 6
Then, the magnification in each operation shown in Table 4 is read out. Then, the variable scale amount determination unit 63
Determines the variable scale amount for the operand value so as not to overflow the computation process even if the read magnification is multiplied by the obtained maximum absolute value of the operand value, and transmits the variable scale amount to the variable scaling unit 62.

When the maximum absolute value of the calculated value is small, the variable scale amount determination unit 63 sets the variable scale amount to a value that scales up the calculated value so that the arithmetic processing does not overflow. To be determined. Then, the variable scaling section 62 scales the operated value based on the transmitted variable scale amount.

As described above, the IMDCT unit 61 determines the variable scale amount in the operand value for each computation process based on the magnification in Table 4 and the maximum absolute value of the input operand value. Has become. When the maximum absolute value is small, that is, when the operated value is data having a small amplitude, the operated value is scaled up.

Therefore, it is possible to improve the accuracy of each operation when the value to be operated is data having a small amplitude. In addition, since the variable scale amount is determined by focusing only on the maximum absolute value, not the entire data of the operated value, the calculation amount for determining the variable scale amount is described in the first embodiment. This is almost the same as the calculation amount of the IMDCT unit 47. Therefore, the IMDCT unit 61
Is configured to determine the variable scale amount with substantially the same power consumption as the IMDCT unit 47.

[Embodiment 3] A third embodiment of the present invention will be described below. The first embodiment described above
The members having the same functions as the members shown in FIGS.
The same reference numerals are given and the description is omitted. The digital recording / reproducing apparatus according to the present embodiment has a configuration in which an IMDCT section 71 is provided instead of the IMDCT section 47 of the audio compression circuit 9 in the configuration of the mini disc recording / reproducing apparatus 1 shown in the first embodiment. .

FIG. 9 is an explanatory diagram showing the configuration of the IMDCT unit 71. As shown in this figure, the IMDCT unit 7
1 includes a scaling unit 72 in place of the fixed scaling unit 55 in the configuration of the IMDCT unit 47 shown in the first embodiment, and a variable scale amount determination unit 63 and a variable scale amount memory 64 shown in the second embodiment. It is a configuration provided with.

The IMDCT unit 71 performs an IMDCT process for each block on the spectrum data input from the inverse quantization unit 46, similarly to the IMDCT unit 47. That is, U in the IMDCT unit 71
(K) The calculation units 51 to y (n) calculation unit 54 perform the following calculation processes (2) to (6) on the input spectrum data.

The scaling unit 72, fixed scale amount loading unit 56, fixed scale amount memory 57, variable scale amount determination unit 63, and variable scale amount memory 64
Is to perform a predetermined scaling on a value to be operated in order to prevent an overflow in the course of the operation before the operation shown in the equations (3) to (5) is performed.

Hereinafter, the scaling of the value to be operated on by the scaling unit 72 will be described. FIG. 1 is a flowchart showing a flow of the operation in the scaling section 72. As shown in FIG.
Inputs the spectrum data input to the U (k) calculation unit 51 (S1). Then, the scaling unit 72
Calculates the maximum absolute value of the scale factor in the input spectrum data (S2).

Then, the scaling section 72 determines whether the scale amount to be used is fixed or variable based on the obtained maximum absolute value (S3 · S).
5). That is, when the obtained maximum absolute value is equal to or greater than a preset first threshold value (for example, 2 ¹⁵ ), the fixed scale amount loading unit 56 is controlled in the same manner as the fixed scaling unit 55 to obtain Read out the fixed scale amount shown in. That is, the fixed scale amount is used for the calculation in the IMDCT unit 71 (S4).

When the obtained maximum absolute value is smaller than the above-mentioned first threshold value and is not less than the second threshold value set in advance (for example, 2 ³ ), the scaling unit 72 changes the variable scaling unit 62. Similarly to the above, the variable scale amount determination unit 63 is controlled to determine the variable scale amount for the operated value for each calculation process. That is, IMD
The variable scale amount is used for the calculation in the CT unit 71 (S6).

Further, if the obtained maximum absolute value is smaller than the above-mentioned second threshold value, the scaling section 72 does not perform scaling on the operated value. That is, I
No scaling is performed in the calculation in the MDCT unit 71 (S7). Then, after S4, S6 or S7, the audio data that has been blocked is output (S7).
8), the process by the IMDCT unit 71 ends.

As described above, the scaling unit 72 in the IMDCT unit 71 is configured to switch the process of determining the scale amount according to the value of the scale factor of the spectrum data. Thereby, the IMDCT unit 71
Can be further improved in comparison with the accuracy of the conversion processing in the IMDCT unit 47 and the IMDCT unit 61.

The scaling in the scaling unit 72 is obtained by adding only the process of determining the maximum value of the scale factor of the spectrum data using the threshold to the process in the fixed scaling unit 55 or the variable scaling unit 62. . For this reason, the difference between the amount of calculation in the scaling unit 72 and the amount of calculation in the fixed scaling unit 55 and the variable scaling unit 62 is so small that it can be ignored. Therefore, the amount of calculation and power consumption of the IMDCT unit 71 are
The amount is almost equal to that of the DCT unit 61. Note that the first and second thresholds are determined according to the amount of calculation and the accuracy of calculation desired by the user.

A program for performing all or a part of processing in the IMDCT unit 71 shown in FIG. 1 is stored in a CD-ROM (Read Only Memory) or an FD (Flop).
An information processing device that can record this program on a recording medium such as a py Disk) and that can input an external digital signal may be used instead of the IMDCT unit 71.

Further, the scaling unit 72 described above
(K) The maximum value of the spectrum data input to the calculation unit 51 may be obtained, and based on this maximum value, it may be determined whether the scale amount is fixed or variable.

The IMDCT unit 47 and the IMDCT unit 6
In the scaling performed in the processing of 1 and the IMDCT unit 71, the scale amount may be set according to the dynamic range accuracy of the scale factor.

The margin bits shown in Table 4 are generated in the upper bits of the data after the operation according to the ratio of the operation data in the operation processing shown in the above equations (3) to (5). There may be.

As described above, according to the first digital signal decoding method of the present invention, a digital input signal is orthogonally transformed into frequency domain spectrum data for each unit time, and the spectrum data is converted into a frequency domain unit. After being divided and the spectrum data of each unit is quantized and coded based on the representative value of the spectrum data of the unit to which it belongs, at least the quantized spectrum data and the representative value of the spectrum data of each unit In a decoding method of digital data for decoding encoded data recorded in a format provided, a representative value of the spectrum data of each unit is searched, and based on the representative value, inverse quantization and inverse orthogonal transform are performed. In order to avoid overflow during the process, schedule with a predetermined fixed scale amount. How to pull up and scale down, and how to scale up and scale down by a variable scale amount corresponding to the operand data,
It is a method of selecting and using.

Further, according to a second digital signal decoding method of the present invention, in the first digital signal decoding method, the scale-up and scale-down may be performed by:
In this method, the maximum value of the representative value of the spectrum data of each unit is searched, and the search is performed based on the maximum value.

According to the first and second digital signal decoding methods, the scale-up and scale-down are performed by a predetermined fixed scale amount based on the representative value of the spectrum data of each unit, or By selecting whether to scale up or down based on the variable scale amount according to the calculation data, the amount of decoding calculation can be reduced compared to the conventional method of scaling up and down using only the variable scale amount. Can be reduced. In addition, the calculation accuracy of decoding can be improved as compared with the conventional method of performing scale-up and scale-down using only a fixed scale amount.

Further, in the third digital signal decoding method of the present invention, in the first digital signal decoding method, a representative value of the spectrum data of each unit is searched for, and based on the representative value. In order to prevent overflow in the process of inverse quantization and inverse orthogonal transform, a method of scaling up and down with a predetermined fixed scale amount and a method of not performing scale up and scale down are selected. This is the method used.

In a fourth digital signal decoding method according to the present invention, in the third digital signal decoding method, the scale-up and the scale-down are performed.
In this method, the maximum value of the representative value of the spectrum data of each unit is searched, and the search is performed based on the maximum value.

According to the third and fourth digital signal decoding methods, scale-up and scale-down are performed by a predetermined fixed scale amount based on the representative value of the spectrum data of each unit, or By selecting whether or not to perform scale-up and scale-down, it is possible to reduce the amount of decoding calculation compared to the conventional method of performing scale-up and scale-down using only a fixed scale amount.

Further, according to a fifth digital signal decoding method of the present invention, in the first digital signal decoding method, a representative value of the spectrum data of each unit is searched for, and based on the representative value. In order to avoid overflow in the process of inverse quantization and inverse orthogonal transformation, select a method of scaling up and down with a variable scale amount according to the data to be operated, and a method of not performing scale up and scale down This is the method used.

A sixth digital signal decoding method according to the present invention is the fifth digital signal decoding method, wherein the scale-up and scale-down are performed by:
In this method, the maximum value of the representative value of the spectrum data of each unit is searched, and the search is performed based on the maximum value.

According to the fifth and sixth digital signal decoding methods, whether to perform scale-up and scale-down based on the representative value of the spectrum data of each unit by a variable scale amount corresponding to the data to be operated on Alternatively, by selecting whether or not to perform scale-up and scale-down, it is possible to reduce the amount of decoding computation as compared with the conventional method of performing scale-up and scale-down using only the variable scale amount.

According to the seventh digital signal decoding method of the present invention, in the first digital signal decoding method, a representative value of the spectrum data of each unit is searched, and the representative value is obtained. Based on the inverse quantization and inverse orthogonal transformation, a method of scaling up and down with a predetermined fixed scale amount and a method of scaling up and down with a variable scale amount according to the data to be operated so that overflow does not occur in the process of inverse orthogonal transformation. This is a method of selectively using a method of performing scale-down and a method of not performing scale-up and scale-down.

An eighth digital signal decoding method according to the present invention is the seventh digital signal decoding method, wherein the scale-up and scale-down are performed by:
In this method, the maximum value of the representative value of the spectrum data of each unit is searched, and the search is performed based on the maximum value.

According to the seventh and eighth digital signal decoding methods, the scale-up and scale-down are performed by a predetermined fixed scale amount based on the representative value of the spectrum data of each unit, or By selecting whether to scale up and down with a variable scale amount according to the calculation data or not to scale up and down, scale up and scale down using only the conventional fixed scale amount Compared to the method
The amount of decoding operation can be reduced and the operation accuracy can be improved. Further, the amount of calculation for decoding can be reduced as compared with the conventional method of performing scale-up and scale-down using only the variable scale amount.

[0165]

As described above, the digital signal decoding method according to the first aspect of the present invention is divided into a plurality of units by the time range and the frequency domain, and the index value set for each unit. A digital signal decoding method for decoding spectrum data encoded for each unit based on the first step of searching for a representative value from index values in each unit; and A second step of determining whether to perform scaling on the operand value in the operation for decoding, and a third step of performing scaling on the operand value based on the determination result in the second step. And a method including:

Thus, according to the above-described method, it is possible to avoid a calculation error due to overflow by scaling and to decode minute amplitude data with high accuracy. Furthermore, since it is determined whether or not to perform scaling, scaling is not performed on data that does not need to be scaled. Therefore, the amount of calculation in the decoding process can be reduced. Further, since this determination is made based on the representative value of the index value in each unit, the processing amount for this determination is very small. As described above, according to the above method, it is possible to improve the accuracy in decoding a digital signal without increasing the amount of calculation.

In the digital signal according to the second aspect of the present invention, in addition to the method according to the first aspect, a scale amount for scaling in the third step is determined based on the representative value. This is a method including a fourth step.

According to the above-mentioned method, all the scale amounts of the arithmetic processing are determined based on the representative values. For this reason, it is possible to determine the scale amount by a very simple process. Therefore, according to this method, in addition to the effect of the first aspect, the digital signal decoding method according to the first aspect can be easily realized, and the operation amount can be further reduced. To play.

According to a third aspect of the present invention, in addition to the method of the first aspect, in addition to the method of the first aspect, a scale amount for scaling in the third step is determined by calculating a scale amount in the operation. This is a method including a fifth step of determining based on a value to be operated.

According to the above method, the scale amount in the arithmetic processing is determined based on the value to be operated which is input data of each arithmetic processing. For this reason, in each operation process, an optimal scaling can be applied to the value to be operated. Therefore, according to this method, in addition to the effect of the first aspect, there is an effect that the accuracy of decoding a digital signal can be extremely increased.

According to a fourth aspect of the present invention, in addition to the method of the first aspect, the digital signal decoding method further comprises the step of:
It is a method including a sixth step of determining whether to determine based on the representative value or a value to be calculated in the calculation, and determining the scale amount based on the determination result.

According to the above method, the method of determining the scale amount is determined according to the spectrum data to be decoded, so that optimal scaling can be performed according to the characteristics of the spectrum data. . Further, since this determination is performed using the representative value, the amount of calculation processing for this determination is very small. Therefore, according to the above method, in addition to the effect of the first aspect, there is an effect that it is possible to perform scaling with an optimal scale amount without increasing the amount of calculation.

According to a fifth aspect of the present invention, there is provided a digital signal decoding method according to any one of the first to fourth aspects, wherein the index value is equal to the spectrum of each unit. In this method, the representative value is the maximum value of the index values of all the units as well as the maximum amplitude value of the data.

According to the above configuration, the representative value becomes the maximum value in the amplitude value of the spectrum data. Therefore, since scaling is performed based on this representative value, it is possible to reliably avoid overflow in arithmetic processing during scaling. Further, according to this method, since the scaling and the maximum value of the index value may be selected to select the index value and the representative value, the selection process can be extremely simplified. As described above, according to the above-described method, in addition to the effects of the first to fourth aspects, there is an effect that it is possible to reliably avoid an overflow in the operation processing without increasing the amount of operation.

In the digital signal decoding method according to the present invention, the digital signal is divided into a plurality of units by a time range and a frequency domain, and each unit is divided based on an index value set for each unit. 7. A method of decoding a digital signal for decoding spectrum data quantized to: a seventh step of searching for a representative value from index values in each unit; An eighth step of scaling the value, and determining whether the scale amount for the scaling in the eighth step is determined based on the representative value or based on a value to be operated on in the operation. Judge,
A ninth step of determining the scale amount based on the determination result.

According to the above-described method, it is possible to avoid a calculation error due to overflow by scaling, and to decode minute-amplitude data with high accuracy. Furthermore, since the method of determining the scale amount is determined according to the spectrum data for decoding, optimal scaling can be performed according to the characteristics of the spectrum data. Further, since this determination is made using the representative value, the amount of calculation processing for this determination is very small. As described above, according to the above method, it is possible to decode a digital signal by optimal scaling without increasing the amount of calculation.

In the digital signal decoding method according to a seventh aspect of the present invention, in the method according to the sixth aspect, the index value is a maximum amplitude value of spectrum data in each unit. The representative value is a method that is the maximum value of the index values of all units.

According to the above method, the representative value becomes the maximum value in the amplitude value of the spectrum data. Therefore, since scaling is performed based on this representative value, it is possible to reliably avoid overflow in arithmetic processing during scaling. Further, according to this method, since the scaling and the maximum value of the index value may be selected to select the index value and the representative value, the selection process can be extremely simplified. As described above, according to the above-described method, in addition to the effect of the sixth aspect, there is an effect that it is possible to reliably avoid an overflow in the operation processing without increasing the amount of operation.

[Brief description of the drawings]

FIG. 1 is a flowchart showing an operation flow of an IMDCT unit in a mini disc recording / reproducing apparatus shown in a third embodiment of the present invention.

FIG. 2 is an explanatory diagram showing a configuration of the mini disc recording / reproducing device shown in the first embodiment of the present invention.

FIG. 3 is an explanatory diagram showing a configuration of an audio compression circuit in the mini-disc recording and reproducing apparatus shown in FIG. 2;

4 is an explanatory diagram showing an example of spectrum data unitized by the audio compression circuit shown in FIG. 3;

5 is an explanatory diagram showing a compression format of audio data output from the audio compression circuit shown in FIG.

FIG. 6 is an explanatory diagram showing a configuration of an audio decompression circuit in the mini-disc recording and reproducing apparatus shown in FIG.

FIG. 7 shows an IMDC in the audio decompression circuit shown in FIG.
FIG. 3 is an explanatory diagram illustrating a configuration of a T unit.

FIG. 8 is an explanatory diagram showing a configuration of an IMDCT unit in an audio decompression circuit of the mini disc recording / reproducing device according to the second embodiment of the present invention.

FIG. 9 is an explanatory diagram showing a configuration of an IMDCT unit in an audio decompression circuit of a mini disc recording / reproducing device according to a third embodiment of the present invention.

FIG. 10 is an explanatory diagram showing a configuration of an audio decompression circuit having a configuration in which scaling is not performed.

11 is an IMD in the audio decompression circuit shown in FIG.
FIG. 3 is an explanatory diagram illustrating a configuration of a CT unit.

[Explanation of symbols]

 Reference Signs List 1 mini disc recording / reproducing device 6 audio compression circuit 9 audio expansion circuit 41 WL expansion section 42 SF expansion section 43 AS expansion section 44 SF maximum value determination section 45 SF offset attaching section 46 inverse quantization section 47 IMDCT section 48 reverse floating section 49 Windowing unit 50 Band synthesis filter unit 51 U (k) calculation unit 52 FFT calculation unit 53 u (n) calculation unit 54 y (n) calculation unit 55 Fixed scaling unit 56 Fixed scale amount loading unit 57 Fixed scale amount memory 61 IMDCT Unit 62 variable scaling unit 63 variable scale amount determination unit 64 variable scale amount memory 71 IMDCT unit 72 scaling unit

Claims (7)

[Claims] A digital signal for decoding spectrum data which is divided into a plurality of units by a time range and a frequency domain and which is encoded for each unit based on an index value set for each unit. A first step of retrieving a representative value from index values in each unit, and a step of determining whether or not to perform scaling on an operation value in an operation for decoding based on the representative value. 2. A method for decoding a digital signal, comprising: a second step; and a third step of performing scaling on a value to be operated on the basis of a result of the determination in the second step. 2. A fourth step of determining a scale amount for scaling in the third step based on the representative value.
2. The method according to claim 1, further comprising the step of: 3. The method according to claim 1, further comprising the step of: determining a scale amount for the scaling in the third step based on a value to be operated on in the operation.
2. A method for decoding a digital signal according to claim 1. 4. The method according to claim 3, wherein a scale amount for scaling in the third step is determined based on the representative value.
6. The method according to claim 1, further comprising the step of: determining whether to determine based on a value to be operated in the calculation, and determining the scale amount based on a result of the determination. Decryption method. 5. The apparatus according to claim 1, wherein said index value is a maximum amplitude value of spectrum data in each unit, and said representative value is a maximum value in index values of all units. A method for decoding a digital signal according to any one of the above. 6. Decoding of a digital signal for decoding spectrum data which is divided into a plurality of units by a time range and a frequency domain and which is encoded for each unit based on an index value set for each unit. A seventh step of retrieving a representative value from index values in each unit; an eighth step of scaling an operation value in an operation for decoding; and a scaling step of the eighth step. Ninth step of determining whether to determine the scale amount for the calculation based on the representative value or the value to be operated on in the calculation, and determining the scale amount based on the determination result. And a decoding method for a digital signal. 7. The apparatus according to claim 6, wherein the index value is a maximum amplitude value of spectrum data in each unit, and the representative value is a maximum value in index values of all units. A method for decoding digital signals.