JPH0236616A - Prediction device - Google Patents

Abstract

PURPOSE:To attain the prediction with high accuracy when an input signal has a periodicity by finding out past input signals whose waveform is similar by means of a correlation coefficient, and using the past signal so as to obtain a prediction value. CONSTITUTION:Signals stored in a storage circuit 2 among signals before a one sample time of a present sampling time or over are X(j-k+1)-X(j-1), a correlation coefficient calculation section 3 calculates (k-L) sets of correlation coefficients P from (j+L-k) to P(j-1) and a mean amplitude ratio AC and outputs the result to a maximum value detection circuit 4. The maximum value detection circuit 4 obtains a time M when the absolute value of the (k-L) sets of correlation coefficients P is maximized and outputs the time M, the correlation coefficient P(M) and the mean amplitude ratio AC(M). Then a multiplier 5 obtains a product among codes of the signal X(M+1), the mean amplitude ratio AC(M) and the correlation coefficient P(M) stored in the storage circuit 2 and the result is outputted from an output terminal 6 as a prediction value XP(j+1) of the input signal at the next sampling time j+1. Thus, the prediction with high accuracy is attained simply.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a technology for predicting digital signals such as voice, music, and images.

[Conventional technology]

An adaptive predictor is a conventional predictor that predicts the input signal at the next sample time from the input signal up to the current sample time. A detailed overview of this method can be found in the theory of ill-defined/adaptive signal processing in ``Theory of Digital Signal Processing'' published by Corona Co., Ltd. Hereinafter, as an example of an adaptive predictor, a prediction principle based on a probability approximation method using a gradient, which is a type of linear prediction method, will be briefly described.

FIG. 3 is a block diagram of a conventional adaptive predictor based on the probability approximation method. 11 is an input terminal, 12 is a storage circuit, 13 is a subtracter, 14 is a prediction coefficient update section, 15 is a prediction value calculation section, 1
6 is a delay device.

The predictor uses the signals before the current sampling time j, i.e.
The input signal X (j+1) at the next sampling time is predicted using the signal from (+1 to j−) to X (j).If the predicted value is set as When the signal E(j) is set as the following equation, E (j) −X (j) −XP (j)
・ ・ ・(2) Power E” (j
) is changed to minimize each coefficient. The power Et(j) of the prediction error signal is E2(j) −(X (j)−XP (j)l
2.
・X(ji-i) (4). Therefore, in order to minimize the prediction error signal power E'' (j), each prediction coefficient Ai (j) is changed as shown below.

A□(j+1)=Ar (j)+g−E (j)・X(
j-4) ... (5) g is a correction coefficient, which is a constant determined according to the characteristics of the input signal, and usually uses a positive value sufficiently smaller than 1.

The signal flow at sample time j will be explained below. The memory circuit 12 receives the signal X (j
) are saved for the number of prediction coefficients. The subtracter 13 subtracts the prediction signal XP(j) from the input signal X(j) to calculate the prediction error E(j) for the input signal at the current sample time. The prediction coefficient update unit 14 calculates the prediction error E according to equation (5).
(j) and the input signal X (+1 to j-) in the memory circuit 12 to the signal from X(j) to predict the prediction coefficient A+(j) to Ak.
(j) is updated and Ak(j+1) is obtained from the new prediction coefficient AI(J+1). The predicted value calculation unit 15 calculates the equation (5
) updated according to prediction coefficient A+(j+1) to Ah
(j+1) and the input signal X (+1 to j-) in the storage circuit 12, the predicted value XP (j+1) of the input signal at the main time of the fire is determined from X(j). The delay device 16 stores the predicted value XP (j+1) used when the subtracter 13 calculates the prediction error signal at the starting time j+1.

[Problem to be solved by the invention]

Conventional adaptive predictors have the disadvantage that high-order prediction coefficients are required for input signals with complex frequency characteristics, which increases the time required for the prediction coefficients to converge.

The purpose of the present invention is to eliminate such conventional drawbacks, and to eliminate the need for convergence time to achieve high prediction accuracy even for signals with complex frequency characteristics as long as the input signal has periodicity. The object of the present invention is to provide a predictor that makes highly accurate predictions.

[Means to solve the problem]

The predictor of the present invention includes a storage circuit for storing input signals, and a correlation coefficient and average amplitude ratio between the latest integer number of input signals in the storage circuit and input signals before a previous sample time in the storage circuit. a maximum value detection circuit that selects the average amplitude ratio and time when the absolute value of the correlation coefficient is maximum; It is characterized by comprising a multiplier that outputs the product of the code and an input signal one sample time after the above-mentioned time as a predicted value of the input signal at the main time.

[Effect]

Past input signals are saved, and a portion whose waveform is similar to the signal near the current sample time is selected from the past signal string. When the input signal has periodicity, it is predicted that the signal part of the main time of the flash will be similar to the signal sequence of the similar part in the past.
A value obtained by multiplying the next signal value of the past similar portion by the average amplitude ratio can be used as the predicted value. By using this predictor, accurate prediction can be made regardless of the frequency characteristics of the input signal.

〔Example〕

FIG. 1 is an embodiment of a predictor according to the present invention.

1 is an input terminal, 2 is a memory circuit, 3 is a correlation coefficient calculation unit, 4
5 is a maximum value detection circuit, 5 is a multiplier, and 6 is an output terminal.

Letting the current sample time be j, a signal X(j) is input from the input terminal 1. The memory circuit 2 stores past signals. That is, the signal X (j-k) is discarded, and the signals from X (+1 to j-) to X (j) are stored in the storage circuit 2. The correlation coefficient calculation unit 3 evaluates the correlation between the L signals from the current sample time j stored in the storage circuit 2 and the signals one sample time before the current sample time j, and calculates the average amplitude ratio. do.

In this embodiment, as a correlation evaluation, a correlation coefficient P (t) is calculated as shown in the following equation.

P (t) = (6) The correlation coefficient P (t) takes a value between -l and 1, and the closer the absolute value is to 1, the more similar the two waveforms are. Also,
When P (t) is positive, the two waveforms are in phase, and when P (t) is negative, they are in opposite phases.

The average amplitude ratio AC(t) is the average value of the amplitude ratios between L signals from the current sample time j stored in the memory circuit 2 and signals one sample time before the current sample time j, and is Use the square root of the power ratio as shown in the formula.

(Σ
1), the correlation coefficient calculation unit 3 calculates P (j+L−k
) to P(j-1), (kL) correlation coefficients P and average amplitude ratios AC are calculated and output to the maximum value detection circuit 4. The maximum value detection circuit 4 determines the time M at which the absolute value of P is maximum from among the (k-L) correlation coefficients P, and determines the time M.

The correlation coefficient P (M) and the average amplitude ratio AC (M) are output. As shown in FIG. 2, the signal values from sample time j-L+1 to current sample time j, that is, the sample ratio value series of the input signal in interval CI, are the signal values from sample time M-L+1 to M, That is, it shows that it is most similar to the sampling ratio value series of the input signal in section C2. If the input signal has periodicity, it is predicted that the signal X (j+1) at the current time of the flash will be similar to the signal X (M+1) at the past sample time M+1, so the average amplitude ratio AC ( The signal X(j+1) is the value obtained by multiplying the sign of the correlation coefficient P (M) by the sign of the correlation coefficient P (M)
can be used as the predicted value signal XP (j+1). Therefore, the multiplier 5 uses the signal X(M+1) stored in the storage circuit 2, the average amplitude ratio AC(M), and the correlation coefficient P.
The product of the signs of (M) is calculated and outputted from the output terminal 6 as the predicted value XP(j+1) of the input signal at the actual spark time j+1.

〔Effect of the invention〕

According to the present invention, parts with similar waveforms are found from past input signals using a correlation coefficient, and a predicted value is obtained using the past signals. Therefore, when the input signal has periodicity, the frequency characteristics of the input signal Therefore, accurate prediction can be performed without requiring convergence time until the prediction accuracy becomes highly accurate.

[Brief explanation of the drawing]

FIG. 1 is a diagram showing an embodiment of the present invention; FIG. 2 is a diagram showing the signal X stored in the memory circuit, FIG. 3 is a diagram showing a conventional adaptive predictor. 1...Input terminal 2...Memory circuit 3... Correlation coefficient calculation section 4...Maximum value detection circuit 5... Multiplier 6...Output terminal

Claims (1)

[Claims] (1) A memory circuit for storing input signals, and a correlation for determining the correlation coefficient and average amplitude ratio between the latest integer number of input signals in this memory circuit and input signals before the previous sample time in the memory circuit. a maximum value detection circuit that selects the average amplitude ratio and time when the absolute value of the correlation coefficient is maximum; and the average amplitude ratio at the time, the sign of the correlation coefficient at the time, and the time. and a multiplier that outputs the product of the input signal after one sample time as a predicted value of the input signal at the next sample time.