JPS5814194A - Adaptive/reverse quantization method and circuit - Google Patents

Abstract

(57) [Summary] This bulletin contains application data before electronic filing, so abstract data is not recorded.

Description

DETAILED DESCRIPTION OF THE INVENTION The present invention relates to an adaptive quantization/adaptive inverse quantization method used for band compression of audio signals, etc., and a circuit thereof.

The adaptive quantization method is a method that expresses the sample value of the input signal with a predetermined number of bits, so-called quantization width is appropriately determined, and it reproduces the input signal level with high precision with a small number of bits. can. Therefore, if such an adaptive quantization method and inverse quantization power coefficient are applied to digital transmission of audio signals, etc., the required number of bits per sample can be reduced compared to the quantization method and inverse quantization without an adaptive function. Since the amount of noise can be reduced compared to when using the conventional method, the transmitted information sound can be reduced, and so-called band compression can be realized.

Among the conventional adaptive quantization and adaptive inverse quantization methods, instantaneous adaptive digitization and instantaneous adaptive inverse quantization related to the present invention will be described in detail below. Instantaneous adaptation amount 5- Details of childization can be found in B published by Ba1l Institute in September 1973.
You can refer to pages 1119 to 1144 of STJ Visit.
The principle is as follows. Now, if the pendulum width at a certain sample time is △j1, then the input signal m at this time is the number of bits for quantization, the output signal is nj, and the quantization width at the next sample time is Decide as follows.

Δj+1=Δj・M(nj) (2) Here, M (n J ) is a multiplier uniquely determined by nj (F), and the audio signal sampled at 13 kHz is divided into 4 bits) (m=4 ) is shown in Table 1.

Table 1 6- Table 1 (Continued) When the quantization width is changed from time to time in this way, the output signal is always 0 when the quantization width is fixed to a constant value, and the output signal The dynamic range of the quantizer can be increased even at large levels where the quantizer is constantly overloaded. Furthermore, if the adaptation amount determined by equation (2) closely follows the input signal, the quantization determined by equation (1) can also be performed with high precision. When applying such a quantizer to a transmission device, the quantized and transmitted signal is subjected to the calculation of equation (2) on the receiving side, and the quantization width at each sample time is reproduced and x , =n, △・+0.5△J (3) j J By inversely quantizing the transmission signal, a signal XJ having approximately the same magnitude as the input signal Xj can be reproduced.

(The quantization width △j on the transmitting side and the receiving side is the initial value Δ0
are equal and there is no error in the transmission path (that is, Jl n
If it is guaranteed that j is always transmitted correctly,
The multiplier M (n j) that multiplies △j on both the sending and receiving sides is the same,
To establish. ) The instantaneous adaptive quantization method described above is suitable for transmitting input signals with high precision and a small number of bits, but the initial quantization width must be the same on the transmitting and receiving sides. In a normal transmission line, the quantization widths on the transmitting side and the receiving side do not match at each sample time because bit errors occur on the transmission line due to line distortion and thermal noise. For information on how to overcome such difficulties, see 1.
“Transactions” published by IEEE in 1975
This method is detailed in onCommunications J, pages 1362 to 1365, and this method replaces equation (2) with equation (4) below.

β △j+1=△j@M'(n) (4) However, β is a number close to 1 but smaller than 1, and M'(n
) is a multiplier that is determined based on the value of n, similar to M(n), and is hereinafter referred to as M(n) for simplicity. The 1/child value at time j obtained by the above correction is nj.Furthermore, β1 is set to a number smaller than 1, so β1 asymptotically approaches 0 as k increases. Based on the above, the initial value is △ on the sending and receiving sides. If it is different, then a. while. Asymptotically approaches ldA: (=1), and Δj+s takes the same value on both sides.Also, when transmission path bit loss occurs, the quantization on the transmitting and receiving sides similarly changes. The widths will be equal.

In other words, if a transmission path pit error occurs at time l, the mismatch in quantization width between the transmitting side and the receiving side that occurs at time l is considered to be a mismatch in the initial values by redefining time l as the initial time. It will be understood that the discrepancy in quantization width due to the above-mentioned transmission path bit error becomes equal on the transmitting side and the receiving side with time.

However, with conventional algorithms that are resistant to transmission bit errors, for signals with a dynamic range of as much as 60 dB, such as audio signals, this is not a problem at average signal levels, but at large signal levels or small At the signal level, this results in deterioration of quantization accuracy. Comparing equations (2) and (3), this is the difference in whether or not △j is raised to the β power, and can be easily understood using the graph of △j vs. △l in Figure 1 as shown below. can. Here, the graph of β=1 means that it is not raised to the β power, and M (n
Corresponds to the calculation of equation (2) except for multiplying by .).

Further, the graph of βゞ1 corresponds to the calculation of equation (4) except that it is multiplied by M(n,). Now, consider a case where the signal level is constantly high. In this case, △ in Figure 1 is △,
However, in a system that uses β to the power which has a strong property against transmission path pitudry, △1 can be reduced to △t by raising to the β power. The difference between (ΔL - Δt) becomes larger as ΔL becomes larger, and this effect is useful when calculating the next quantization width Δ, +, which is really necessary. It becomes a factor that occurs. For this reason, encoding accuracy deteriorates for signals with high signal levels.

Similarly, the signal level is constantly low and becomes a big candy. For this reason, the level is lowered and signal sample values are less likely to suffer from loss of digits due to quantization, which worsens the encoding accuracy. In addition, if the value of β is brought close to 1, the deterioration in encoding accuracy for high-level or low-level signals can be reduced, but the mismatch between the quantization widths on the transmitting side and the receiving side due to transmission path bit errors can be resolved for a long time. It will remain without.

The purpose of the present invention is to perform adaptive quantization that eliminates the mismatch between quantization widths on the transmitting side and the receiving side in a short time in response to bit errors on the transmission path, and maintains high coding accuracy even for high-level and low-level signals. An object of the present invention is to provide an adaptive inverse quantization method and circuit.

The adaptive Doji conversion and dequantization method of the present invention adaptively determines the quantization width at the next sample time using the quantization reference value, the quantization width at the current sample time, and the quantization code. In adaptive quantization and inverse quantization methods that adaptively perform quantization and inverse quantization using quantization widths, multiple quantization width candidates at the next sampling time are generated using the quantization reference value of the count. Then, the input signal level is estimated from the quantization code obtained so far, and one of the plurality of quantization width candidates is selected in response to the estimated value of the input signal level, and the next sample time is selected. The feature is that the quantization width is determined at .

Further, the adaptive quantizer of the present invention includes an inverse quantization circuit that inversely quantizes a quantization code input at each sampling time, a multiplier whose multiplicand is the output of the inverse quantization circuit, and a multiplier that uses the output of the inverse quantization circuit as a multiplicand. a level detector for estimating an output signal level from a quantization code; a coefficient predetermined value generation circuit for calculating a plurality of multiplier values corresponding to a plurality of different quantization reference values; The present invention is characterized by comprising means for selecting one of the plurality of coefficient expected value generation circuit outputs according to the output and outputting it to the multiplier terminal of the multiplier at the next sampling time.

Further, the adaptive inverse quantizer of the present invention includes a divider that takes a sampled and digitized input signal as a dividend, a quantization circuit that quantizes the output of the divider, and a a level detector for estimating an input signal level; a coefficient predetermined value generation circuit for calculating a plurality of said divisor values corresponding to a plurality of different quantization reference values; and a means for selecting one of the outputs of the coefficient predetermined value generation circuit and outputting it to the divisor terminal of the divider at the next sampling time. Detailed explanation.

First, the adaptive quantization and inverse quantization method of the present invention will be explained with reference to FIG.

The principle of the present invention is to define the quantization width at the next sampling time corresponding to equation (2) or equation (4) as follows. To determine whether to determine ΔS□ or ΔS□, the signal level of the input signal is calculated from the output of the adaptive quantizer, and Δ5i, which is close to the input signal level, is used.

For this reason, in order to find the number 8 from Δj corresponding to FIG.
/Δsi) βΔ, i is graphed as shown in FIG. In FIG. 2, it is assumed that △81〈△,2, and △ corresponding to FIG. 1 is also shown by a broken line. As is clear from Figure 2, in the graph of (△j/△si)β△81, in the conventional method, the graph of △a intersected with the graph of △j at LO, but instead of △, □, and △ There will be two graphs with the intersection points moved in parallel to the two locations of S2. One of the two graphs will be used, but this selection does not change depending on the sample time, but rather the short-time energy of the input signal (the energy calculated using the counted sample values) Therefore, for an input signal with a high signal level, a graph passing through Δs1 is used, and for an input signal with a low signal level, a graph passing through Δs1 is used to determine the next sample time. Determine the quantization width in . For example, if we consider a case where a high level signal is constantly input, there is a high probability that △ near △L in FIG. 2 will occur.

△ vs. △ in Figure 2 that determines the quantization width at the next sample time
Using the graph of 1-h/M to find △1=△L, the new method gives △L'', and the conventional method gives △L. Obviously, △L'' is better than △(y). For this reason, the new method can achieve quantization that is less susceptible to overloading even for high-level input signals.For low-level signals, the new method uses a graph that intersects △j at △, l. ,Δj
-h/M is calculated, so in this case as well as in the case of high-level signals, a significant improvement can be expected compared to the conventional method. In the new method, the adaptability of the quantization width at the next sampling time is worse than in the conventional method near Δ1=1, 0, but the degree of deterioration is much smaller than the improved value when Δj=ΔL. If the input signal is a signal such as voice, where there are individual differences or the voice level changes from time to time even for the same person, the new method of adaptive quantization is more accurate over a wide range of input signal levels. This means that it can be quantized.

It can be understood that the new quantization method is also resistant to transmission line bit errors as follows. Now at △ and □ in Figure 2, △
It is assumed that the doji conversion width at the next sample time is determined using a graph that intersects with , and that a transmission path bit error occurs in this state. From now on, when determining the quantization width at the next sampling time using the same graph in FIG.
+t =M (wine +1ri...
...The value approaches 1 when the can is opened, and the quantization width becomes the same on both the sending and receiving sides.

Next, transmission line bit errors affect not only the instantaneous quantization width mismatch but also the energy level calculation of the input signal, so that from the next sampling time the Δ
Let us consider the case where the quantization width is determined using the graph intersecting △j in step 5. In this case, even if it is assumed that no error occurs in the transmission signal at the next sampling time, the following difference occurs in the quantization width determination between the transmitting side and the receiving side.

As mentioned above, β is given a value close to 1, so the formula (
8) is a value close to 1. The difference in the quantization width between the transmitting side and the receiving side is very small, and even if the quantization width is changed using a different graph in FIG. 2 for calculating the signal energy, there will not be a large difference. Therefore, if the true input signal level deviates slightly to one side from the vicinity of the threshold for determining which graph in Figure 2 should be used to determine the next quantization width, the energy on the transmitting and receiving sides will decrease. It is determined that the same graph in FIG. 2 should be used for both calculation results. If this point is considered as the initial point, the difference in quantization width between the transmitting side and the receiving side will be canceled at each new sampling time according to the same formula as in (7). The time it takes to correct the quantization widths on the transmitting side and the receiving side using the different graphs in FIG. 2 is short, but the quantization widths on the transmitting side do not match. However, as is clear from Equation 5 (8), the difference in the quantization width between the two is very small, and as a result, the difference between the transmitted signal X and the received signal 9□ is also small, and no major deterioration occurs.

In the method of the first invention, in realizing the formula (61), △
A part that calculates △j+1 using $1 and a part that calculates △-1 using △s2 are provided in parallel, and the quantization code n
The input signal level is inferred from .

In addition, in the method of the second invention, in order to realize equation (6), 1
8- Estimate the input signal level from the quantization code nj,
Select one of △s1, △, 2, then △j+,
has been decided.

As described above, by using the new adaptive quantization and adaptive inverse quantization methods, it is possible to perform highly accurate quantization and inverse quantization while having the same level of robustness against transmission line bit errors as conventional methods.

Although the present invention has been explained using two quantization width reference values, the case where two or more quantization width reference values are used can also be easily inferred.

Further, similar effects can be expected when the adaptive quantization method of the present invention is applied to a differential encoding method or the like.

Next, the present centrifugal quantizer will be explained with reference to FIG.

The adaptive quantizer shown in FIG. 3 includes a divider 2 whose dividend is a sampled digitized input signal, a quantization circuit 3 that quantizes the output of this divider 2, and a quantizer 3 that quantizes the output of this divider 2. Corresponding to the level detector 7 which estimates the input signal level from the output of j183 and the plurality of quantization reference values p,
Depending on the outputs of the coefficient expected value generation circuits 5 and 6 that calculate the number of divisor values and the level detector 7, one of the outputs of the plurality of coefficient expected value generation circuits 5 and 6 is selected, and the next sample is selected. and means for outputting the output to the divisor terminal of the divider 2 at the time. In Fig. 3, divider 2 is manufactured by RCA company 1979.
1-C037MO8Memories, M published in August
icroprocessors and Support
t Systems J, pages 140 to 150. In addition, although the details of the quantization circuit 3 will be described later, a plurality of threshold values (for example, 2"-1) are set for the digitized input signal.
, and converts it into an output signal expressed as . The details of the structures of the first coefficient expected value generation circuit 5 and the second coefficient expected value circuit 6 will be described later, but the same circuits can be used. Quantization width reference values Δs1 and Δ5 . applied to terminals 9 and 10, respectively. are used to independently generate coefficients corresponding to the quantization width at the next sampling time. Also,
The details of the level detector 7 will be described later, but it calculates the short-term energy of the input signal X from n. The selection circuit 8 is based on [The Bipolar Digital] published by Japan Texas Instruments Co., Ltd. in 1981.
Integrated Circuits Data
IC described in 7-169 to 7-175 negative of BookJ
It can be composed of

Now, at a certain time j, X is applied to the input terminal 1, and the output of the selection circuit 8 is the current doji conversion width △.

If ZX is output, the output of divider 2 will be )J/
△, is output. For the quantization circuit 3, n, ≦x,
/△,<(n,+1), , m such that 191
The bit sign n is output from terminal 4. In this case, equation (9) is n, ・j≦x <(n +1)△ (10
)1 j j and matches formula (1). Output n of the quantization circuit 3.

Output Δ5 of selection loop 8. Input signal △81 from quantization width reference signal input terminal 9 In first coefficient expected value generation circuit 5, °(△J/△81)β△sIM(n) (11
) is calculated and output. Similarly, the output nj of quantizer 3 is 2
1- Output of selection circuit 8 △5. Quantization width reference signal input terminal 10
From the input signal △, 2, the second coefficient expected value generation port j1
In 86, (△, /△sz)'4S2M(nl) (12
) is calculated and output. Further, the output of the doji converter 3 is multiplied by the output signal Δj of the selection control path 8 in the signal level detector 7 to reproduce the input signal and calculate its energy. When the calculated energy value becomes larger than a predetermined value (for example, (△, l + △82) / 2), the signal level detector 7 applies a signal to the selection terminal S of the selection circuit 8 and selects the next sampling time. The output of the second coefficient expected value generation circuit 6 is transmitted to the output of the selection circuit 8, and on the other hand, if the energy calculation value is smaller than the predetermined value, the first coefficient expected value is transmitted at the next sampling time. The output of the generation circuit 5 is controlled to be transmitted to the output of the selection circuit 8. The reason why the adaptive quantization circuit shown in Figure 3 is resistant to transmission line bit damage and can perform highly accurate quantization is as follows.
The output of the quantization circuit 3 is expressed by equation (10) which is equal to equation (1), and the modulus of the quantization width at the next sampling time is the first coefficient 22-numerator constant which is equal to equation (6). Formula (I]) which is the output of the generating circuit 5 and the second
It will be clear from the equation (121) which is the output of the coefficient expected value generation time M6 that the actual average is set, and from the details described in the above-mentioned section on the principle of the present invention.

Next, the configuration of the pendulum circuit 3 used in FIG. 3 will be described. In the following, for the sake of simplicity, a case will be described in which an input signal equivalent to 4 bits is quantized into an output signal of 2 bits. The quantization circuit 3 can use a read-only memory IJ (ROM), for example,
Published by 8ignics in 1979 (D [sign
etics Bipolar & MO8Memory
R described in Data Manual J pages 66-69
Can be configured with OM. A 4-bit input signal is supplied to the lower 4 bits of the address input terminal of the ROM, and a 2-bit output signal is outputted from the lower 2 bits of the ROM output terminal. The contents are shown in Table 2. However, it is assumed that the input signal applied to the address has a small point between the 2nd and 3rd bits from the LSB as a signal value, and the quantization circuit output cuts this into an integer value. I think of it as something to throw away.

The structure of the coefficient expected value generation circuits 5 and 6 shown in FIG. 3 is shown in FIG. In FIG. 4, coefficient expected value generation circuits 5 and 6, quantization code input terminal 11, quantization width reference input terminal 12, current quantization width input terminal 13, and multiplier generation circuit 14 are shown.
, divider 15, β multiplication calculation circuit 16, multipliers 17 and 1
8. Each of the output terminals 18 is connected to the [
LS Multipliers data 5he
It can be configured with the multiplier described in etJ. Further, the multiplier generating circuit 14 can use the ROM used in the quantization circuit 3 shown in FIG.
). Furthermore, the β-power calculation circuit also has the above-mentioned RO
M is available. In this case, decimal numbers are also allowed for the input signal, so if the numerical expression is expressed in m bits and the decimal point is in the l bit from the LSB, the input signal is multiplied by 21 to the address of the integer. It is better to store the value of the signal raised to the β power.

Now, when the quantization width Δ at time j is input from the terminal 13 and the quantization width reference signal Δ5 is input from the terminal 12, the divider 15 calculates and outputs Δj/Δ. This signal is added to the β-power calculation circuit 16, and as an output (△
j/△8) Obtain a signal that is β. This signal is multiplier 1
7 is multiplied by △S added from multi-terminal 12 (△j
/△, ) β△. On the other hand, the quantization code n inputted from the terminal 11 is inputted to the multiplier generation circuit 14, and M(n
, ) and are applied to the multiplier 18. In the multiplier 18, this signal is multiplied by the output signal of the multiplier 17, and the output terminal 19 receives (△).

/ΔS)βΔ5・M(nt) is output.

FIG. 5 is a block diagram of the level detector 7 used in FIG. In the figure, the level detection circuit 7 includes a quantization code input terminal 201, a quantization width input terminal 21, an inverse quantization circuit 22, multipliers 23 and 24, a digital low-pass filter 25, a comparator 26, and a comparison reference value input terminal 27. , and an output terminal 28. In FIG. 5, multipliers 23 and 24
The same hardware as multipliers 17 and 18 in FIG. 4 can be used. Details of the configuration of the digital low-pass filter 25 can be found in Prentice-Hall, 1975.
Inc, Englewood C11ffs.

Theory and published by New Jersey
Appli-cation of Digital
30th of “Signal Processing”
See Fig. 5.10 on page 6. Comparator 26U19
[The Bipolar DigitalInteg] published by Japan Texas Society Instruments Co., Ltd. in 1981
rated C1rcuits Data BookJ
15-220 to 15-221. The inverse quantization circuit 22 is the quantization circuit 3 in FIG.
The same ROM can be used, and Table 3 shows the ROM contents of the inverse quantization circuit corresponding to Table 2. However, for the contents of the ROM, a small point is placed at the second and third bits from the LSB. As a result, for the input nj, n 1 +1 /
2) is output, and the value obtained by dividing equation (3) by Δj is reproduced.

Table 3 Now, consider the case where quantization code n is input to the input terminal 20 in FIG. The quantization code nj is increased in majority value representation precision (bit number) by the inverse quantization circuit 22, and this signal is multiplied by the quantization width Δ, added from the terminal 21 by the multiplier 23, and becomes the human signal X, Reproduce. This reproduced signal X.

is multiplied to the 92nd power by the multiplier 24 and inputted to the low-pass filter 25 before (x:, i=0.1...
...j)'s DC component is extracted. In this way, the output obtained by passing the square value of the input signal through a low-pass filter represents the short-term energy of that signal. This filter 25
The output signal of is compared with a comparison reference value by a comparator 26,
When the filter output signal is larger than the reference value, °°1" appears at the output terminal 28, and conversely, when it is smaller, IIO" appears at the output terminal 28.

As described above, according to the present invention, it is possible to realize an adaptive quantizer that is resistant to transmission path bit errors and capable of highly accurate quantum encoding.

The fixed quantization circuit 3 in FIG. 3 used for explaining the present invention is shown in Table 2.
Accordingly, a linear quantization circuit that satisfies Equation (1) is realized, but if the nature of the input signal is determined in advance, the quantization accuracy can be further improved by using a non-linear quantization circuit. In this case, non-linear quantization is possible by changing the number of consecutive pieces of data that have the same content in the ROM content shown in Table 2. Even if such a change is made, as is clear from the principle of the present invention described above, the advantages of the present invention, such as being strong against bit errors in the transmission line and performing quantization with high accuracy, are not lost. Therefore, such changes are also part of the invention.

The coefficient expected value generation circuit shown in FIG. 4 used to explain the present invention is as follows:
Xβ was executed directly using ROM, but this operation was
The present invention also includes a method in which Taylor expansion is performed in the vicinity of =l and approximation is performed using the first few terms. For example, if Xβ is Taylor-expanded using the first two terms, then Xβ=1+βX (131), so the expression (6) can be simplified as follows.

Even if the coefficient generator is of the type that undergoes this @ expression transformation, the transmission line pi Hk! which is the eleventh point of the present invention! resistant to
The property of highly accurate quantization is preserved.0 The level detector of FIG. 5 used in the present invention has a quantization code n
The energy key subtraction was performed by regenerating the input signal using a tJ circuit, but as the signal level increases, the quantization circuit tends to be overloaded, and as the signal level decreases, Since drop-offs tend to occur in a short time even in adaptive quantization circuits, it is also possible to immediately square the % quantization code nj30- and pass it through a low-pass filter. In this case, the inverse quantization circuit 22, multiplier 23, and terminal 21 in FIG. It is also possible to perform energy key calculation based on the above-mentioned changes.The advantages of the present invention, which are strong against transmission line bit errors and highly accurate quantization, remain the same.

Note that the coefficient expected value generation circuits 5 and 6 shown in FIG. It can also be realized by a coefficient expected value generation circuit. For this purpose, a selection circuit jiiS (the structure is the same as the selection circuit 8) which selects △, 1 or △8□ with the output of the level detector 7 is used.
It is sufficient to add the quantization width reference value input terminals of the coefficient predetermined value generation circuits to the quantization width reference value input terminals of the coefficient predetermined value generation circuits and immediately transmit the output of this coefficient predetermined value generation circuit to the divider 2.

The above explanation has been made using two quantization width reference values △8□ and △,2, but the case of two or more can be similarly realized.

Next, the adaptive inverse quantization circuit of the present invention will be explained with reference to FIG. The adaptive dequantization circuit shown in FIG. 6 is a dequantization circuit 3 that dequantizes the quantization code input at each sampling time.
1 and a multiplier 3 whose multiplicand is the output of the inverse quantization circuit 31.
6, a level detector 34 that estimates the output signal level from the input quantization code, and a coefficient expected value generation circuit 32 that calculates a plurality of multiplier values corresponding to a plurality of different quantization reference values. and 33, and selects one of several coefficient predetermined value generation circuit outputs according to the output of the level detector 34,
Means 3 for outputting to the multiplier terminal of the multiplier 360 at the next sample time
It consists of 5. The inverse quantization circuit 31 has the same configuration as the inverse quantization circuit 22 shown in FIG. First coefficient expected value generation circuit 32 and second coefficient expected value generation circuit 3
3 have the same configuration as the coefficient predetermined value generation circuits 5 and 6 shown in FIG. 3, and the circuit shown in FIG. 4 can be used. The level detector 34 is the same as the level detector 7 shown in FIG. 3, and the circuit shown in 1L FIG. 5 can be used. The selection circuit 35 is the same as the selection circuit 8 in FIG. 3, and the multiplier 36 is the same as the selection circuit 8 in FIG.
It is the same as 3.

When a quantization code n is input to the first terminal 30.

The inverse quantization circuit 31 converts the pits into several with increased representation precision (pit count) and multiplies them by the quantization width Δj at this time. According to the explanation of FIG. 5, since the output of the quantization circuit 31 was (ni+1/2), the output terminal 39 was (
n j + 1 / 2 ) Δj is output, and X in equation (3)
, will be output.

On the other hand, in the coefficient expected value generation circuit 32, the quantization width to be used at the next sample time is determined from △4 input to terminal A, n5 input to terminal B, and △, 1 input to terminal C. (by the action △/△ f・′・△・M(n,) 4 31 51 J) and outputs more than one terminal.

Similarly, at the coefficient scheduled value generation time j833, the quantization width to be used at the next sampling time is set to 13 from △3 input to terminal A, n5 input to terminal B, and △ input to terminal C. It is calculated by the calculation (△, /△5□)β・△82・M(・饅, and outputs more than the terminal.

In addition, the level detector 34 measures the energy of X by reproducing the quantization code n and the quantization width △j (j) The determination result is provided to the selection circuit 35. The selection circuit 35 uses the width. It is explained in detail in the detailed description of the present invention that the adaptive inverse quantization circuit having such a configuration is resistant to the effects of pit errors in the transmission line and can perform inverse quantization with high accuracy. Furthermore, in the adaptive inverse quantization circuit, as described in the configuration of the adaptive quantization circuit, the quantization circuit 31 is changed to a nonlinear inverse quantization circuit, and the calculations are tailored in the coefficient predetermined value generation circuits 32 and 33. Simple method using expansion approximation, level detector 34
Changes such as simplification of calculations can be applied.

Note that the coefficient expected value generation circuits 3234- and 33 shown in FIG. This can be realized with one coefficient predetermined value generation circuit. For this purpose, the quantization width reference value △5 is determined by the output of the level detector 34. It is sufficient to provide a selection circuit for selecting either one of and △5□, and transmit the output directly to the multiplier 36.

Although the adaptive inverse quantization circuit also uses two quantization width standards, it can be similarly implemented using two or more quantization width standards.

Further, adaptive quantization and inverse quantization can be used in combination with various other band compression methods, and the use of the principles of the present invention even in the use of such a combination is part of the present invention. An example of such a combination is differential encoding, in which a predictor is used to predict the sample value of the next sample, and the difference between the input signal and the child result is quantized and transmitted. Those that use the principles of the invention are also part of the invention.

Similar effects can be obtained even when the 35- conversion circuit is implemented as software for a signal processing microprocessor, which is a part of the present invention.

[Brief explanation of the drawing]

FIG. 1 is an explanatory diagram of the conventional adaptive quantization and inverse quantization method, FIG. 2 is an explanatory diagram of the adaptive quantization and adaptive inverse quantization method of the present invention, and FIG. 3 is an explanatory diagram of the adaptive quantization and inverse quantization method of the present invention. FIG. 4 is a detailed diagram of a part of FIG. 3, FIG. 5 is a detailed diagram of a part of FIG. 3, and FIG. 6 is a block diagram of an adaptive inverse quantizer of the present invention. . In Fig. 3, 2...divider, 3...
- Quantization circuit, 5, 6...-- Coefficient predetermined value generation circuit, 7... Level detector, 8...-... Selection circuit. In FIG. 6, 31...inverse quantization circuit, 32
and 33...coefficient generation circuit, 34...
・Level test / [D △7. ．． /-OAm, Δ
J note 7 figure △st /-D △52
Δmu Otsuj Note 5 Note 5 41st 5 [fl 2nd

Claims (1)

[Claims] 1. Adaptively determines the quantization width at the next sampling time using the quantization reference value, the quantization width at the current sampling time, and the quantization code, and adapts using this quantization width. In adaptive unification and inverse quantization methods that perform quantization and inverse quantization, multiple quantization reference values are used to generate multiple candidates for the quantization width at the next sample time. Estimate the input signal level from the obtained quantization code, select one of the plurality of quantization width candidates in response to the estimated value of the input signal level, and perform quantization at the next sample time. An adaptive quantization and adaptive inverse quantization method characterized in that a width is determined. 2. Adaptively determine the quantization width at the next sample time using the quantization reference value, the quantization width at the current sample time, and the quantization code, and use this quantization width to adaptively perform dojiization and inversion. In adaptive quantization and inverse quantization methods that perform quantization, a plurality of quantization reference values are estimated, an input signal level is estimated from the quantization codes obtained so far, and an estimated value of the input signal level is calculated. in response to selecting one of the plurality of prepared quantization reference values, and calculating the next sample time from the selected quantization reference value and the 1° quantization and quantization code at the current sample time. Adaptive quantization and adaptive inverse quantization methods characterized by determining the quantization width in . 38 A divider whose dividend is a sampled and digitized input signal, a quantization circuit that quantizes the output of the divider, and a level detector that estimates the input signal level from the output of the quantization circuit.
a coefficient predetermined value generation circuit that calculates a plurality of said divisor values corresponding to a plurality of different quantization reference values; and an output of said plurality of said coefficient predetermined value generation circuits in accordance with the output of said level detector. 1. An adaptive quantization circuit comprising: means for selecting one of the following and outputting it to a divisor terminal of the divider at the next sampling time. 4. a divider whose dividend is a sampled and digitized input signal; a quantization circuit that digitizes the output of the divider; and a level detector that estimates the input signal level from the output of the quantization circuit; The quantization width reference value is selected from among a plurality of predetermined quantization reference values according to the output value of the level detector, and is set as the quantization width reference value. Adaptive quantization circuit. 5. A dequantization circuit that dequantizes the quantization code input to the Yanagimoto time conversion circuit; a multiplier that uses the output of the dequantization circuit as a multiplicand; and an output signal level from the quantization code input to fnj. a level detector for estimating the multiplier values; a coefficient expected value generation circuit for calculating the plurality of multiplier values in response to a plurality of different quantization reference values; 1. An adaptive inverse quantization circuit comprising means for selecting one of the outputs of the expected value generation circuit and outputting it to the multiplier terminal of the multiplier at the next sampling time. 6. An inverse quantization circuit that inversely quantizes the quantization code input at each sampling time; a multiplier that uses the output of the inverse quantization circuit as a multiplicand; and an output signal level based on the input quantization code. a level detector for estimating, and means for selecting one of a plurality of predetermined quantization reference values according to the output value of the level detector and setting it as the quantization width reference value. An adaptive inverse quantization circuit that takes this as a % characteristic.