JPH043695B2 - - Google Patents

Description

[Detailed description of the invention]

The present invention relates to an ADPCM circuit that alternately repeats PCM encoding and ADPCM encoding, and particularly to an ADPCM decoding circuit that does not accumulate quantization noise.
For details regarding ADPCM, please refer to "Proceedings of IEEE" published by IEEE in April 1980, pages 488-525.
In addition, regarding an improved ADPCM with characteristics that are resistant to bit errors on the transmission path, the May 1982 IEEE
Published “Proceeding of ICASSP′82” page 960~
Details on page 963. Hereinafter, ADPCM will be explained based on the second document to the extent necessary for explaining the present invention. Figure 1 shows a conventional ADPCM code and decoding circuit, including an input signal terminal 1, a subtracter 2, an adaptive quantization circuit 3, an inverse adaptive quantization circuit 4, an adder 5, an adaptive prediction circuit 6, and a code output. Consists of terminal 7
The figure shows an ADPCM decoding circuit including an ADPCM code circuit, a code input terminal 8, an inverse adaptive quantization circuit 9, an adder 10, an adaptive prediction circuit 11, and an output terminal 12. The adaptive quantization circuit 3 is a circuit that obtains an output signal with a length of N bits smaller than M when the input signal is expressed with a length of M bits ^.
-1 threshold value is used for judgment, and the judgment result is output in N bits. In other words, if the quantization width at a certain sample time j is △ _j , the input signal x _j at this time is n _j・△ _j x _j <(n _j +1)・△ _j , n _j ∈{0, ±1, ± 2,...±(2 ^N-1 -1), -2 ^N-1 } (1) If N is the allocated number of quantization bits, the output signal is n _j , and the output signal at the next sampling time (j+1) is The quantization width Δj ₊₁ is companded using the following equation according to the input signal level of the adaptive quantization circuit. △ _j+1 = △〓 _j・M(n _j ) (2) Here, M(n _j ) is a multiplier uniquely determined by n _j , and the audio signal sampled at 8kHz is converted into 4 bits ( Table 1 shows an example of the multipliers used when encoding N=4).

[Table] In Equation (2), if β is set to be a positive constant rather than 1, as long as the adaptive prediction circuit is a time-invariant filter, the calculation of △〓 _j has the effect of leaking the past quantization width, so it is not transmitted. It is known that it is resistant to bit errors.For details, please refer to "Transactions on Communications" published by IEEE in 1975, pages 1362 to 1365. Inverse adaptive quantization circuit 4
and 9 outputs an M-bit reproduced input signal in accordance with the threshold value when the N-bit output signal of the adaptive quantization circuit 3 and the transmitted N-bit quantization circuit output signal are input. Then, the transmitted signal is dequantized by x^ _j =n _j △ _j +0.5△ _j (3). This x^ _j is called the representative value. Since the quantization characteristics shown by equations (1) and (3) have a constant width between threshold values, the width between representative values is also constant, and is called a linear quantization characteristic. In general, the width between threshold values and the width between representative values are not constant, and they usually have widths that depend on the statistical distribution function of the signal to be quantized, which will be described in detail later. The transfer functions of the adaptive prediction circuits 6 and 11 are the same, and if this is P(Z), then P(Z)= _k 〓 ⁱ⁼¹ a ^j _i Z ^-i (4). Here, {a ^j _i |i=1,...,k} is time j
If the predictor input signal at time j is x^ _j and the inverse quantizer output signal is e^ _j , each coefficient is changed so that e^ _j ² is minimized. That is, it is known that each coefficient should be changed from time to time as a ^j+1 _i = (1-δ)a ^j _i +g·e^ _j ·x^ _ji (5). Here, δ and g are positive constants smaller than 1. Below, according to Figure 1, the conventional ADPCM code circuit,
The decoding circuit will be described. When the input signal sample value x _j at time j is input to the ADPCM encoding circuit from terminal 1, the difference between the input signal x _j and the output signal x〓 _j of the adaptive prediction circuit 6 is calculated by the subtracter 2, and the error signal
It is input to the adaptive quantization circuit 3 as e _j . As described above, the adaptive quantization circuit 3 converts e _j into an N-bit code n _j , which is output from the terminal 7 and simultaneously input to the inverse adaptive quantization circuit 4. The inverse adaptive quantization circuit 4 reproduces an M-bit error signal e^ _j from _nj . The reproduced error signal e^ _j and the output x〓 _j of the adaptive prediction circuit 6 are added by an adder 5 to reproduce the quantized input signal x^ _j . After this, the quantization width of the adaptive quantization circuit 3 and the inverse adaptive quantization circuit 4 and the adaptive prediction circuit 6 are determined.
The coefficients of are modified to encode the next input signal as described above. As mentioned above, the coefficient correction of the adaptive prediction circuit is based on the power of the error signal e^ _j , that is, e^ ² _j
Since the dynamic range of the e _j signal is smaller than that of the x _j signal, the dynamic range of the e j signal is smaller than the The errors that occur are also reduced, allowing for highly accurate encoding. On the other hand, in the conventional ADPCM decoding circuit, the received quantization code n _j is inputted from the terminal 8, and the inverse adaptive quantization circuit 9 generates the reproduction error signal x^ _j . This e^ _j and the output x〓 _j of the adaptive prediction circuit 11 are added by the adder 10, and x^ _j is combined and output to the output terminal 12, and the next sample time is predicted to the adaptive prediction circuit 11. Add for. On the ADPCM decoding circuit side, the quantization width of the inverse adaptive quantization circuit is changed moment by moment according to equation (2 ₎ from the adaptive quantization code n _j or the error signal e^ _j , _and The coefficients of the adaptive prediction circuit 11 are calculated using equation (5) to minimize the difference, that is, the power of e^ _j .
Change according to. In the ADPCM encoding circuit and decoding circuit, if the internal states of the inverse adaptive quantization circuits 4 and 9 and the adaptive prediction circuits 6 and 11 match, e^ _j , x^ _j , x〓 of the ADPCM encoding circuit/decoding circuit The values of _j match. For this reason
Even if the ADPCM encoding circuit and the decoding circuit are provided at a distance, the input signal x _j applied to the terminal 1 and the x^ _j output from the terminal 12 take almost the same value. Incidentally, the line between the terminal 7 of the encoding circuit and the terminal 8 of the decoding circuit is a transmission line, and there is a possibility that bit errors may occur in the transmission line due to thermal noise or the like. In this case, the ADPCM decoding circuit often falls into an unstable state and cannot recover. This can be explained as follows. Output of inverse adaptive quantization circuit 9 of ADPCM decoding circuit
The transfer function D(Z) from e^ _j to output terminal 12 is
When the transfer function of the adaptive prediction circuit 11 is determined using equation (4), becomes. As mentioned above, a ^j _i is a value calculated from e^ _j , and when a transmission path bit error occurs, the correction value of the prediction coefficient of the prediction circuit adapted to the ADPCM decoding circuit is
This value is different from the prediction coefficient of the adaptive prediction circuit of the ADPCM code circuit. Equation (6) has K poles determined by the prediction coefficients, and as a result of the above transmission line bit error, the pole position may move outside the unit circle on the Z plane on the ADPCM decoding circuit side. . In such a situation, the ADPCM decoding circuit enters an oscillating state and cannot return to normal operation again. (The second
In the second document, in order to eliminate this unstable state, Equation (6) is expanded as shown below to create an ADPCM encoding circuit and decoding circuit with a transfer function that excludes adaptively moving poles. has been realized. Here, the coefficient {a^ _i is a fixed constant, and {b ^j _i } is an adaptive coefficient. The term (1+ _M 〓 ⁱ⁼¹ b ^j _i Z ^-i ) transforms equation (6) into (1
− _k 〓 ⁱ⁼¹ a^ _i Z ^-i ) is divided by the (M+1) term. If the fixed coefficient {a^ _i } is selected to a value that suits the average nature of speech, the above-mentioned truncation error will be small, and there will be almost no deterioration in encoding quality. Here, the method for determining the fixed coefficient {a^ _i } that matches the average nature of speech is detailed on page 498 of the above-mentioned first document. FIG. 2 shows a conventional ADPCM encoding circuit and decoding circuit based on equation (7). Figure 2 shows input terminal 1,
Consists of subtracters 21 and 22, adaptive quantization circuit 3, inverse adaptive quantization circuit 4, adders 51 and 52, adaptive filter 61, fixed filter 62, and output terminal 7
ADPCM code circuit, input terminal 8, inverse adaptive quantization circuit 9, adders 101, 102, adaptive filter 1
11, a fixed filter 112, and an output terminal 12. Fixed filter 62
and 112 have the following transfer function with the fixed prediction coefficients {a^ _j } used in equation (4). P2(Z)= _M 〓 ⁱ⁼¹ a^ _i Z ^-i (8) Furthermore, the adaptive filters 61 and 111 have the following transmission function. P1(Z)= _k 〓 ⁱ⁼¹ b ^j _i Z ^-i (9) However, each adaptation coefficient is modified as follows,
The second document states that this is corrected to minimize the power of the e _j signal. b ^j+1 _i = (1-δ)b ^j _i +ge^ _ji e^ _j (10) Now, when input signal x _j is input from terminal 1,
The subtracter 21 takes the difference from the output x〓 _j of the fixed filter 62 to obtain y _j , which is input to the subtracter 22. The subtracter 22 subtracts the output y〓 _j of the adaptive filter from y _j ,
It is added to the adaptive quantization circuit 3. The adaptive quantization circuit 3 quantizes e _j and outputs the code n _j from the output terminal 7, which is also applied to the inverse adaptive quantization circuit 4 to obtain a quantized error signal e^ _j . e^ _j is input to the adaptive film 61 and used for filter calculation at the next sampling time, and the output of the adaptive filter 61
y〓 _j is added by an adder 51 and is transmitted to an adder 52 as y〓 _j . The adder 52 adds y^ _j and _x〓j to reproduce the quantized signal x^ _j of the input signal _xj , which is used for filter operation at the next sampling time. Therefore, if the output of the fixed filter 62 is suitable for the average behavior of the input signal, the first error signal
The amplitude level of y _j decreases, and the second error signal e _j obtained by subtracting the output of the adaptive filter 61 from this signal becomes a signal with an even lower level. Generally speaking, the adaptive prediction circuit 6 in FIG. 1 predicts the next input signal value from the reproduced quantized input value, whereas the adaptive filter 61 in FIG. 2 predicts the next input signal value from the error signal. Although the adaptive filter 61 in FIG. 2 has a lower ability to predict, since the fixed filter 62 generates a signal related to the characteristics of the average input signal, the encoder in FIG. is also the first overall
Compared to the encoder shown in the figure, it is possible to perform encoding that is less complex than the encoder shown in the figure. Next, the operation of the ADPCM decoding circuit shown in FIG. 2 will be explained. When the quantization code is input from the input terminal 8, the inverse adaptive quantization circuit 9 reproduces the quantized error signal e^ _j , inputs it to the adaptive filter 111, and uses it for the adaptive filter calculation at the next sample time. and adder 10
1, the output y〓 of the adaptive filter 111 is added to _j
Play y^ _j . y^ _j is the output x〓 _j of fixed filter 112
The encoder measurement input signal x^ _j which is added and quantized by the adder 102 is reproduced and supplied to the output terminal 12 and the fixed filter 112. Adaptive filter 11
1 and the transfer function P1 (Z) of the fixed filter 112 and
P2(Z) is as shown in equations (8) and (9), and the transfer function D(Z) from the output of the inverse adaptive quantization circuit 9 to the output terminal 12 is D(Z)=1+P1(Z) /1−P2(Z) (11), which is consistent with equation (7), and the adaptively moving pole is Z
Since it is not held on a flat surface, stable operation can be expected even if transmission line bit errors occur. In addition to the above, the ADPCM encoding/decoding circuit may have an adaptive zero point/adaptive pole shape prediction filter that uses the fixed filters 62 and 112 shown in FIG. The details are omitted as they can be explained easily. We have looked at the ADPCM encoding/decoding circuit above, but when considering introducing this ADPCM circuit into an existing PCM network, as shown in Figure 3, the signal encoded with PCM will be encoded with ADPCM again.
A form that is PCM encoded and transmitted occurs. Third
The figure shows a case where two stages of ADPCM encoding/decoding circuits are connected in cascade. As a result, a situation occurs in which PCM encoding and ADPCM encoding are performed alternately. Generally, the calculations inside the ADPCM encoder/decoder circuit are as follows:
When 8-bit nonlinear PCM is linearized, it becomes equivalent to 14 bits, so a linear code of 14 bits or more is used to perform encoding comparable to PCM. Therefore, the ADPCM encoding/decoding circuit and other
If the ADPCM encoding/decoding circuit can be connected with linear code bits that are equal to or greater than the number of ADPCM internal operation bits, even if the ADPCM encoding/decoding circuits are connected in cascade, there will be no deterioration due to the connection itself. For this reason, the first ADPCM code/signal circuit and the subsequent
If the internal states of the ADPCM code/signal circuits all match, even if ADPCM code/decoding circuits are connected in cascade, the internal states will change in the same way in the ADPCM code/decoding circuits, no matter how many stages they are connected in cascade. , the deterioration of the ADPCM circuit is limited to one stage. However, as described above, the ADPCM encoding/decoding circuit and the following ADPCM encoding/decoding circuit are connected by a nonlinear 8-bit PCM code. For this reason, when cascaded, the number of usable bits decreases, and the connection itself deteriorates due to non-linear weighting of each bit in the number of usable bits. Deterioration due to this connection itself is due to the initial
Even if the internal states of the ADPCM encoding/decoding circuit and the following ADPCM encoding/decoding circuit match at a certain point in time, the selected ADPCM codes will differ because the input PCM codes differ by the amount of degradation. choice
If the ADPCM code is different, the multiplier shown in Table 1 given by the adaptive quantization equation (2) will be different, and
Since the adaptive prediction coefficients of equations (5) and (10) become different, the internal states become inconsistent. Therefore, in the case of cascade connection, in addition to the deterioration due to the PCM connection, the deterioration due to the ADPCM encoding/decoding circuit is accumulated by the number of cascade connection stages, resulting in very large deterioration. Regarding the above mechanism in which the coincidence of internal states collapses, the relationship between the threshold value and the representative value of the quantization circuit used in the ADPCM encoding/decoding circuit is expressed by equations (1) and (3). As long as it has the characteristics, the IEEE 1979 “Proceedings of
1979 ISCAS”, pages 969 to 970, and once the internal states match, the threshold interval and the representative value interval match, which is the property of linear quantization. (See Table 2 of the same document). However, conventional internal state maintenance methods are not suitable for ADPCM with nonlinear quantization characteristics, which is commonly used to improve quantization ability. It cannot be applied to encoding/decoding circuits.This nonlinear quantization characteristic examines the statistical distribution of the signal input to the quantization circuit and determines a threshold value and representative value suitable for this distribution.For example, a distribution function When is a Gaussian distribution, and the number of quantization code bits is 4, it is determined as shown in Table 2, according to 7 of "Transactions on Information Theory" published by IRE May 1960.
Details are given on pages 1-12.

[Table] As is clear from Table 2, the inter-threshold interval and the representative value interval are not constant widths, unlike the linear quantization characteristics given by equations (1) and (3). For this reason, the conventional method of maintaining coincidence of internal states using constant threshold intervals and representative value intervals is no longer applicable, and ADPCM encoding/decoding circuits with such quantization circuits are converted to nonlinear PCM encoding. When connecting in cascade via , an accumulation of characteristic degradation occurred. The object of the present invention is to have nonlinear quantization characteristics.
An object of the present invention is to provide an ADPCM decoding circuit in which characteristic deterioration does not accumulate even if the ADPCM encoding/decoding circuit is subjected to nonlinear PCM encoding. Another object of the present invention is to provide a method that does not depend on the structure of the adaptive prediction circuit of the ADPCM code/decoder circuit or the quantization characteristics of the adaptive quantization circuit, and does not accumulate characteristic deterioration during cascade connection. The ADPCM decoding circuit according to the present invention is an ADPCM encoder that adaptively quantizes a residual signal, which is the difference between a signal obtained by linearizing an input nonlinearly encoded PCM signal and an adaptively predicted prediction signal, at each sample time. In the ADPCM decoding circuit that receives the output code signal and outputs the nonlinear PCM decoded signal,
From the quantization code signal from the ADPCM encoder, a representative residual signal, a low limit residual signal, and a high limit residual signal are generated corresponding to the residual signal on the encoder side, and the quantization code an inverse adaptive quantization circuit that determines the quantization characteristic at the next sampling time based on the signal; and the representative residual signal from the inverse adaptive quantization circuit;
an addition means that adds an adaptive prediction signal to be described later to generate a representative decoded signal; a nonlinear PCM conversion circuit that converts the representative decoded signal into a nonlinear encoded PCM; and a linear PCM conversion circuit that linearizes the output of the nonlinear PCM conversion circuit.
a PCM conversion circuit, a subtraction means for subtracting an adaptive prediction signal, which will be described later, from an output signal of the linear PCM conversion circuit to generate a representative decoded residual signal, the representative decoded residual signal, the low limit residual signal, and means for converting the output signal of the nonlinear PCM converter as it is or by adding +1 or -1 to a nonlinear PCM decoded signal by comparing the high limit residual signals; It is composed of at least an adaptive prediction circuit that inputs a representative residual signal, generates an adaptive prediction signal at the current time, and determines the prediction characteristics at the next sample time, and outputs a representative residual signal from the adaptive inverse quantization circuit. This ADPCM decoding circuit is characterized in that it outputs not only a residual signal but also high and low extreme residual signals, and uses these values to modify the nonlinear PCM code of a representative decoded signal to produce a nonlinear PCM decoded signal. The present invention will be described in detail below with reference to the drawings. FIG. 4 shows an embodiment of the ADPCM circuit shown in FIG. 2 of the present invention, including an input terminal 8, an inverse quantization circuit 91, adders 101 to 104, and a subtracter 105.
~106, adaptive filter 111, fixed filter 1
12, linear-nonlinear PCM conversion circuit 120, nonlinear-linear PCM conversion circuit 121, comparison circuit 123,
It consists of a selection circuit 124, an output terminal 126, an adaptive filter 111, a fixed filter 112,
Adders 101 and 102 are the same as the ADPCM decoding circuit shown in FIG. Also, linear-nonlinear
Details of the PCM conversion circuit 120 and nonlinear-linear PCM conversion circuit 121 were published in September 1970 by Bell System.
The one described in "BSTJ" published by Laboratories, pages 1555-1588 can be used. When the inverse adaptive quantizer 91 receives the input ADPCM code n, it calculates the representative value, threshold value, and n+ corresponding to n shown in Table 2.
A value obtained by multiplying each of the threshold values of 1 by the quantization width _Δj is output, and in this way, the representative value takes a form that represents the interval indicated by both threshold values. If n is 8, then n
A sufficiently large number as a +1 threshold (e.g. 10000)
Establish and use it virtually. Assuming that an ADPCM code n _j is now input to the terminal 8, the inverse adaptive quantization circuit 91 multiplies the representative value and threshold value shown in Table 2 corresponding to the ADPCM code n _j by the current quantization width △ _j . Output the value. This output signal includes a representative residual signal e^ _j corresponding to the residual signal e _j on the encoder side, and a value indicating both limits of the signal value interval represented by this representative residual signal e^ _j . The larger one is THU and the smaller one is THL. Since the adaptive filter 111 and the fixed filter 112 are outputting the predicted value at the current time (the total sum is P _{j )} , the adders 101 and 10
2, the adaptive filter 111 and the fixed filter 11
By adding the two predicted output values, a representative decoded signal x^ _j is obtained. Therefore, the following formula holds. x^ _j = e^ _j + P _j (12) Here again, the representative decoded signal x^ _j is the interval (TEL + P _j ,
THU + P _j ). Representative decoded signal x^ _j is linear-nonlinear PCM converter 1
20, it is converted into a normal 8-bit PCM code X. Furthermore, after X is again converted into a PCM quantized signal x^ ^R _j by the nonlinear-linear PCM converter 121,
The subtracters 105 and 106 allow the adaptive filter 11
1 and the predicted output value of the fixed filter 112 at the current time, it is converted into a representative decoded residual signal e ^R _j and input to the comparator 123 . Therefore, the representative decoded residual signal e ^R _j is given by the following equation. e ^R _j =x ^R _j −P _j (13) Now, consider when e ^R _j exists within the interval [THL, THU). In this situation, the comparator 123 selects and outputs the PCM code X by the selection circuit 124. Assuming that the internal state of the ADPCM code circuit at the next stage is the same as the internal state of the current stage, x ^R _j is used as a linear input in the ADPCM code circuit at the next stage, and e ^R _j is the interval [THL , THU) are assigned the same ADPCM code as the current stage. Therefore, the internal states of the ADPCM encoding/decoding circuits at the current stage and the next stage are the same. Next, e ^R _j is not in the interval [THL, THU) and e ^R _j >
Consider the case of THU. The input signal of the current stage ADPCM encoding circuit is also a nonlinear PCM signal, and the value obtained by PCM quantizing the representative decoded signal x^ _j is x ^R _j , and e ^R _j
Since the relationship between and x ^R _j is expressed by equation (13), there should be at least one representative value of PCM in the interval [THL+P _j , THU+P _j ). (If the PCM representative value is not in this interval, this interval is
ADPCM code should not be selected. ) Furthermore, since the value obtained by PCM quantizing the representative value x^ _j in the interval [THL+P _j , THU+P _j ) is x ^R _j
The quantization threshold of PCM exists at [THL + P _j , x^ _j ], and since x ^R _j > THU + P _j , the quantization width of PCM is between 2 (x ^R _j −x^ _j ) and 2 (x ^R _j − It will be understood that such a situation occurs when the quantization width of PCM becomes _from one to at most twice the quantization width of ADPCM. In such a case, the difference between the nonlinear PCM code X that generated x ^R _j and the input nonlinear _PCM code of the current ADPCM code circuit is
P _j , THU + P _j ), and it is clear that X is a higher PCM code by 1 than x ^R _j is absent. In addition, since the nonlinear PCM code has a special polarity amplitude expression, the comparison circuit 123 activates the selection circuit 124 in this situation, and when x ^R _j is positive (the MSB of the nonlinear PCM code X that generated x ^R _j ( Most S
ignificant B it) is 1), the adder 103 adds +1 to X (minimum step size), and when it is negative (corresponds to when the MSB of X is 0), the adder 104 adds -1 to X. In order to select a signal as an output, the input PCM signal of the current stage ADPCM code circuit and
It will be understood that the input signals of the next-stage ADPCM code circuit become completely equal, and the coincidence of internal states is maintained. Furthermore, e ^R _j is not in the interval [THL, THU), that is, x ^R _j is not in the interval [THL+P _j , THU+P _j ).
Consider the case where e ^R _j <THL. In this case as well, at least one PCM representative value is in the interval [THL+P _j ,
THU + P _j ). Also, since the value obtained by PCM quantizing the representative value x^ _j in this interval is x ^R _j , the PCM quantization threshold is [x^ _j , THU +
P _j ). Therefore, the quantization width of PCM is 2
(x^ _j −x ^R _j ) ~ 2 (THU + P _j + x ^R _j ), and it can be understood that this also occurs when the quantization width of PCM becomes from 1 times to at most the quantization width of ADPCM. . In such a case, the nonlinear PCM that generated x ^R _j
Code X and the input nonlinearity of the current ADPCM code circuit
The difference from the PCM code is that X is smaller by 1 PCM
It is obvious that it is a code. Therefore, in this situation, the comparison circuit 123 selects the selection circuit 124.
When x ^R _j is positive (corresponding to when the MSB of X is 1), adder 104 adds -1 to
(equivalent to when the MSB is 0) is selected as the output by +1 in the adder 103, so
Input PCM signal of ADPCM code circuit and next stage
The input PCM signals of the ADPCM code circuit become completely equal, and the internal states remain consistent. Note that the operations of the adaptive filter 111 and the fixed filter in FIG. 3 are as described using FIG. 2 as a description of the conventional ADPCM. As described above, according to the present invention, even if ADPCM encoding/decoding circuits are connected in multiple stages via PCM encoding/decoding circuits, if the internal states of the ADPCM encoding/decoding circuits match, the ADPCM encoding/decoding circuit It is possible to realize an ADPCM decoding circuit having a property that the characteristics deteriorate only by one stage. Further, although the present invention has been explained in FIG. 4 with respect to the ADPCM circuit of FIG. 2, it can be easily applied to the ADPCM circuit of FIG. 1 as well. Furthermore, the prediction filter 112 in the ADPCM circuit of FIG.
is a fixed filter, but even if it is an adaptive filter, it does not change the essence of the present invention. Furthermore, for easy analogy, the output of the inverse adaptive quantization circuit 91 is e^ _j , (THL−e^ _j ), (THU−e^ _j )
The present invention also includes a method in which e ^R _j is obtained by subtracting x^ _j from x ^R _j such that the length is the representative value and the length from the representative value to the limit value.

[Brief explanation of drawings]

Figure 1 is a block diagram showing a conventional ADPCM encoding/decoding circuit, and Figure 2 is a block diagram showing a conventional ADPCM encoding/decoding circuit.
Figure 3 is a block diagram showing the decoding circuit. Figure 4 is a block diagram showing the cascade connection of ADPCM code/decoding circuits.
The figure is a block diagram showing an ADPCM decoding circuit according to the present invention. In the figure, 91...inverse adaptive quantization circuit, 11
1...Adaptive filter, 112...Fixed filter,
101-104... Adder, 105-106...
Subtractor, 120...Linear-nonlinear PCM converter,
121...Nonlinear-linear PCM converter, 123...
. . . comparison circuit, 124 . . . selection circuit.

Claims (1)

[Claims] 1. Adaptively quantize the residual signal, which is the difference between the linearized input nonlinear encoded PCM signal and the adaptively predicted prediction signal, at each sample time.
In an ADPCM decoding circuit that receives a code signal output from an ADPCM encoder and outputs a nonlinear PCM decoded signal, the quantization code signal from the ADPCM encoder corresponds to the residual signal on the encoder side. , an inverse adaptive quantization circuit that generates a representative residual signal, a low limit residual signal, and a high limit residual signal, and determines a quantization characteristic at the next sampling time based on the quantization code signal; an addition means that adds an adaptive prediction signal, which will be described later, to the representative residual signal from the adaptive quantization circuit to generate a representative decoded signal; a nonlinear PCM conversion circuit that converts the representative decoded signal into a nonlinear encoded PCM; a linear PCM conversion circuit that linearizes the output of the nonlinear PCM conversion circuit; a subtraction means that subtracts an adaptive prediction signal, which will be described later, from an output signal of the linear PCM conversion circuit to generate a representative decoded residual signal; By comparing the difference signal with the low limit residual signal and the high limit residual signal, the nonlinear PCM converter output signal is converted into a nonlinear PCM converter as it is or by adding +1 or -1.
a means for generating a decoded signal; and inputting the representative decoded signal or the representative decoded signal and the representative residual signal to generate an adaptive prediction signal at the current time, and
It is composed of at least an adaptive prediction circuit that determines the prediction characteristics at the next sample time, and outputs not only the representative residual signal but also the high and low extreme residual signals as the output of the adaptive inverse quantization circuit. An ADPCM decoding circuit characterized in that a nonlinear PCM code of a representative decoded signal is modified to produce a nonlinear PCM decoded signal.