EP1700293B1 - Schema de codage predictif - Google Patents

Schema de codage predictif Download PDF

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Publication number
EP1700293B1
EP1700293B1 EP04804095A EP04804095A EP1700293B1 EP 1700293 B1 EP1700293 B1 EP 1700293B1 EP 04804095 A EP04804095 A EP 04804095A EP 04804095 A EP04804095 A EP 04804095A EP 1700293 B1 EP1700293 B1 EP 1700293B1
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information signal
value
speed parameter
adaption
values
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EP1700293A1 (fr
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Gerald Schuller
Manfred Lutzky
Ulrich Krämer
Stefan Wabnik
Jens Hirschfeld
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Fraunhofer Gesellschaft zur Forderung der Angewandten Forschung eV
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Fraunhofer Gesellschaft zur Forderung der Angewandten Forschung eV
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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
    • G10L19/16—Vocoder architecture
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
    • G10L19/16—Vocoder architecture
    • G10L19/18—Vocoders using multiple modes
    • G10L19/24—Variable rate codecs, e.g. for generating different qualities using a scalable representation such as hierarchical encoding or layered encoding
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/02—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders
    • G10L19/022—Blocking, i.e. grouping of samples in time; Choice of analysis windows; Overlap factoring
    • G10L19/025—Detection of transients or attacks for time/frequency resolution switching
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L2019/0001—Codebooks
    • G10L2019/0013—Codebook search algorithms
    • G10L2019/0014—Selection criteria for distances

Definitions

  • the present invention relates to the predictive coding of information signals, e.g. Audio signals, and more particularly to adaptive predictive coding.
  • a predictive coder - or transmitter - encodes signals by predicating a current value of the signal to be coded by the past values of the signal.
  • this prediction is based on the current value of the signal by a weighted sum of the past values of the signal.
  • the prediction weights or prediction coefficients are continuously adapted to the signal, so that the difference between the predicted signal and the actual signal is minimized in a predetermined manner.
  • the prediction coefficients are optimized, for example, with respect to the square of the prediction error.
  • the error criterion when optimizing the predictive coder or else the predictor can also be chosen differently. Instead of using the least squares criterion, the spectral flatness of the error signal, i. differences or residuals.
  • the decoder or receiver Only the differences between the predicted values and the actual values of the signal are transmitted to the decoder or receiver. These values are called residuals or prediction errors.
  • the actual signal value can be reconstructed by using the same predictor and thus adding the predicted value to the prediction error obtained in the same way as the encoder, which has indeed been transmitted by the encoder.
  • the prediction weights for the prediction can be adapted to the signal at a predetermined speed.
  • LMS Least Mean Squares
  • the parameter must be set in a manner that is a compromise between the rate of adaptation and the precision of the prediction coefficients.
  • This parameter sometimes referred to as a step size parameter, thus determines how fast the prediction coefficients adapt to an optimal set of prediction coefficients, where a non-optimally adjusted set of prediction coefficients results in the prediction being less accurate and hence the prediction errors larger again at an increased bit rate for transmission of the signal, since small values or small prediction errors or differences with fewer bits can be transmitted than larger ones.
  • the document US6104996 describes an adaptive predictive encoder which switches the order of the order depending on the characteristics of the signal to be coded.
  • the predictors i. the prediction algorithms, the transmitter side and the receiving side at a given, for both sides of the same time points to a certain state reset, which is referred to as reset.
  • the object of the present invention is to provide a scheme for the predictive coding of an information signal, on the one hand a sufficient robustness against errors in the difference values or residuals of the coded information signal and on the other hand, a lower associated increase in the bit rate or reducing the signal quality.
  • the present invention is based on the finding that it must be deducted from the previous fixed setting of the speed parameter of the adaptive prediction algorithm on which a predictive coding is based, towards a variable setting of this parameter. Namely assuming an adaptive prediction algorithm controllable by a velocity coefficient to operate with a first adaptation velocity and a first adaptation precision and a first prediction precision associated therewith in the case where the velocity coefficient has a first value the speed parameter has a second value, with a second, compared to the first lower adaptation speed and but a second, to work against the first higher precision, so can the occurring after the reset times adaptation periods in which the prediction error due to the not yet adapted prediction coefficients are initially increased, decreasing by the speed parameter first set to the first value and after a while to the second value. After the speed parameter has been set to the second value after a predetermined period of time after the reset times, the prediction errors and thus the residuals to be transmitted are optimized or smaller than would be possible with the first speed parameter value.
  • the present invention is based on the finding that prediction errors after reset instants can be minimized by setting the velocity parameter, such as the velocity parameter.
  • the step size parameter of an LMS algorithm is changed for a certain period of time after the reset times so that the speed of adaptation of the weights for this duration is increased with admittedly reduced precision.
  • Fig. 1 shows a predictive encoder 10 according to an embodiment of the present invention.
  • the encoder 10 includes an input 12 at which it receives the information signal s to be encoded, and an output 14 at which it outputs the encoded information signal ⁇ .
  • the information signal may be any signal, such as an audio signal, a video signal, a measurement signal, or the like.
  • the information signal s consists of a sequence of information values s (i) with i ⁇ lN, ie audio values, pixel values, measured values or the like.
  • the coded information signal ⁇ is composed of a sequence of difference values or residuals ⁇ (i) with i ⁇ IN, which correspond to the signal values s (i) in the manner described below.
  • the encoder 10 comprises a prediction device 16, a subtracter 18 and a control device 20.
  • the prediction device 16 is connected to the input 12, as described in more detail below, for a current signal value s (n) a predicted value s '(n) from previous signal values s (m) with m ⁇ n and MYN and output at an output, which in turn is connected to an inverting input of the subtractor 18.
  • a non-inverting input of the subtractor 18 is also connected to the input 12 to subtract the predicted value s' (m) from the actual signal value s (n) - or simply to form the difference of the two values - and the result at the output 14 as a difference value ⁇ (n) output.
  • the predictor 16 implements an adaptive prediction algorithm. In order to perform the adaptation, it therefore receives the difference value ⁇ (n) - also called prediction error - via a feedback path 22 at another input.
  • the prediction device 16 comprises two control inputs, which are connected to the control device 20. Via these control inputs, it is possible for the control device 20 to initialize prediction coefficients or filter coefficients ⁇ i of the prediction device 16 at specific times, as will be described below, and to modify a velocity parameter of the prediction algorithm on which the prediction device 16 is based referred to as.
  • a step 40 first the control device 20 initializes the prediction or filter coefficients ⁇ i of the prediction device 16.
  • the initialization after step 40 takes place at predetermined reset times.
  • the reset times, or more precisely the signal value numbers n, in which a reset was performed after step 40, may occur, for example, at fixed time intervals to one another.
  • the reset times can be reconstructed on the decoder side, for example by incorporating information about them into the coded information signal ⁇ , or by standardizing the fixed time interval or the fixed number of signal values between them.
  • the coefficients ⁇ i are set to any values that are the same, for example, at every reset time, ie, at each execution of step 40.
  • the prediction coefficients are initialized to values heuristically derived from typical representative information signals, and in this regard, on average, ie, the representative set of information signals, such as a mixture of jazz, classical, rock, etc. pieces of music optimal set of prediction coefficients.
  • a step 42 the controller 20 sets the speed parameter ⁇ to a first value, wherein steps 40 and 42 are preferably performed substantially simultaneously with the reset timings.
  • steps 40 and 42 are preferably performed substantially simultaneously with the reset timings.
  • the setting of the speed parameter to the first value has the consequence that the prediction device 16 carries out a rapid adaptation of the prediction coefficients ⁇ i initialized in step 40-with an admittedly reduced adaptation precision.
  • step 44 the prediction device 16 and the subtracter 18 then act together as prediction device in order to code the information signal s and in particular the current signal value s (n) by prediction thereof by adapting the prediction coefficients ⁇ i .
  • step 44 comprises a plurality of substeps, namely the determination of a predicted value s' (n) for the current signal value s (n) by the prediction device 16 using previous signal values s (m) with m ⁇ n using the current prediction coefficients ⁇ i , subtracting the thus predicted value s' (n) from the actual signal value s (n) by the subtractor 18, outputting the resulting difference value ⁇ (n) at the output 14 as part of the coded information signal ⁇ , and adapting or adaptation of the coefficients ⁇ i by the prediction device 16 on the basis of the prediction error or difference value ⁇ (n) which it receives via the feedback path 22.
  • the prediction device 16 uses the speed parameter ⁇ predetermined or set by the control device 20, which, as will be described in more detail below with reference to the exemplary embodiment of an LMS algorithm, determines how strongly the feedback is determined Prediction error ⁇ (n) per adaptation iteration, here n, enters into the adaptation or updating of the prediction coefficients ⁇ i or how much the prediction coefficients ⁇ i change depending on the prediction error ⁇ (n) per adaptation iteration, ie per feedback ⁇ (n) can.
  • step 46 the control device 20 then checks whether the speed parameter ⁇ should be changed or not.
  • the determination in step 46 may be performed in several ways. For example, the controller 20 determines that a speed parameter change should be made, if the initialization or setting in step 40 or 42 has passed a predetermined period of time. Alternatively, the controller 20 evaluates, for determination in step 46, a degree of adaptation, such as the approximation to an optimal set of coefficients ⁇ i with a corresponding low mean prediction error, to the predictor 16, as will be explained in more detail below.
  • step 46 the control device 20 checks whether there is again a reset time, ie a point in time at which the prediction coefficients should be reinitialized for resynchronization reasons. First, it is again assumed that there is no reset time. If there is no reset time, then the prediction device 16 continues with the coding of the next signal value, as indicated by "n ⁇ n + 1" in FIG.
  • the encoding of the information signal s is continued by adapting the prediction coefficients ⁇ i with the adaptation speed, as set by the speed parameter ⁇ , until, finally, during a passage of the loop 44, 46, 48 in the step 46, the control device 20 determines that a speed parameter change should be made. In this case, the control device 20 sets the speed parameter ⁇ to a second value in a step 50.
  • the setting of the speed parameter ⁇ , to the second value has the result that the prediction device 16, when passing through the loop 44-48 in step 44, the adaptation of the prediction coefficients ⁇ i from now on with a lower adaptation speed, but with an increased adaptation precision, such that in these passes following the speed parameter change timing, which refer to subsequent signal values of the information signal s, the resulting residuals ⁇ (n) decreases, which in turn allows for an increased compression rate in incorporating the ⁇ (n) values into the encoded signal.
  • step 48 After further runs of the loop 44-48 then the controller 20 will eventually recognize a reset time in step 48, after which the function sequence begins again at step 40.
  • the decoder is shown in Fig. 3 by reference numeral 60. It comprises an input 62 for receiving the coded information signal ⁇ consisting of the difference values or Residuals ⁇ (n), an output 64 for outputting the decoded information signal ⁇ which corresponds to the rounding error in the representation of the difference values ⁇ (n) the original information signal s (n) and accordingly from a sequence of predecoded signal values ⁇ (n), a predictor 66 identical or functionally identical to that of the coder 10 of FIG.
  • An input of the predictor 66 is connected to the output 64 to obtain already decoded signal values s (n). From these already decoded signal values s (m) with m ⁇ n, the prediction device 66 determines a predicted value s' (n) for a signal value s (n) currently to be decoded and outputs this predicted value to a first input of the adder 68.
  • a second input of the adder 68 is connected to the input 62 to sum the predicted value s' (n) with the difference value ⁇ (n) and the result or the sum to the output 64 as part of the decoded signal ⁇ and output the input of the predictor 66 for prediction of the next signal value.
  • Another input of the predictor 66 is connected to the input 62 to obtain the difference value ⁇ (n), which uses this value to adapt the current prediction coefficients ⁇ i .
  • the prediction coefficients ⁇ i can be initialized by the control device 70, just as the speed parameter ⁇ can be varied by the control device 70.
  • steps 90 and 92 corresponding to steps 40 and 42 first the control device 70 initializes the prediction coefficients ⁇ i of the prediction device 66 and adjusts the speed parameter ⁇ thereof to a first value which corresponds to a higher adaptation speed but to a reduced adaptation precision.
  • step 94 the prediction device 66 then decodes the coded information signal ⁇ or the current difference value ⁇ (n) by predicating the information signal by adapting the prediction coefficients ⁇ i . More specifically, step 94 includes several substeps. First, the prediction device 66, which is informed of the already decoded signal values s (m) with m ⁇ n, predicts therefrom the signal value currently to be determined, in order to obtain the predicted value s' (n). In this case, the prediction device 66 uses the current prediction coefficients ⁇ i .
  • the difference value ⁇ (n) currently to be decoded is added to the predicted value s' (n) by the adder 68 in order to output the sum thus obtained as part of the decoded signal ⁇ at the output 64.
  • the sum is also input to the prediction means 66, which will use this value s (n) in the next prediction.
  • the prediction means 66 uses the difference value ⁇ (n) from the coded signal stream to adapt the current prediction coefficients ⁇ i , the adaptation speed and the adaptation precision being predetermined by the currently set speed parameter ⁇ . In this way, the prediction coefficients ⁇ i are updated or adapted.
  • step 96 the controller checks whether a speed parameter change has to take place. If this is not the case, in a step 98 corresponding to the step 48, it is determined by the control device 70 whether there is a reset time. If this is not the case, the loop of steps 94-98 is run through again, this time for the next signal value s (n) or the next difference value ⁇ (n), as indicated by "n ⁇ n + 1" in FIG. 4 is indicated.
  • step 96 if there is a speed parameter change timing, in a step 100, the controller 70 sets the speed parameter ⁇ to a second value that corresponds to a lower adaptation speed but a higher adaptation precision, as already discussed with respect to coding.
  • FIGS. 1-4 Having described generally a predictive coding scheme according to an embodiment of the present invention with reference to FIGS. 1-4, a specific embodiment for the predicting means 16 is described with reference to FIGS. 5-7, namely according to which embodiment the predicting means 16 according to FIG an LMS adaptation algorithm works.
  • Fig. 5 shows the structure of the prediction means 16 according to the LMS algorithm embodiment.
  • the prediction device 16 comprises an input 120 for signal values s (n), an input 122 for prediction errors or difference values ⁇ (n), two control inputs 124 and 126 for the initialization of the coefficients ⁇ i or the setting of the speed parameter ⁇ and an output 128 for the output of the predicted value s' (n).
  • the prediction device 16 comprises a transversal filter 130 and an adaptation control 132.
  • the transversal filter 130 is connected between input 120 and output 128.
  • the adaptation controller 132 is connected to the two control inputs 124 and 126 and also to the inputs 120 and 122 and further comprises an output for forwarding correction values ⁇ i for the coefficients ⁇ i to the transversal filter 130.
  • the transversal filter 130 receives at an input 140 the sequence of signal values s (n).
  • the input 140 is followed by a series connection of m delay elements 142, so that at connection nodes between the m delay elements 142 the signal values s (n-1)... S (nm) are present, which precede the current signal value s (n).
  • the estimate s' (n) in a relatively stationary environment approximates a value predicted after the solution in Vienna, as the number of iterations reaches n infinity.
  • the adaptation controller 132 is shown in greater detail in FIG. 7.
  • the adaptation controller 132 accordingly comprises an input 160, at which the sequence of difference values ⁇ (n) is received. These are multiplied in a weighting device 162 with the speed parameter ⁇ , which is also referred to as a step size parameter.
  • the result is applied to a plurality of m multipliers 164, which multiply the same by one of the signal values s (n-1) ... s (nm).
  • the results of the multipliers 164 form correction values ⁇ i ... ⁇ m .
  • the correction values ⁇ i ... ⁇ m represent a scalar version of the inner product of the estimation error ⁇ (n) and the vector of signal values s (n-1)...
  • the scaling factor ⁇ which is used in the adaptation controller 132 and, as already mentioned, also referred to as step size parameter, can be regarded as a positive quantity and should satisfy certain conditions relative to the spectral content of the information signal, so that the LMS algorithm, which is realized by the device 16 of Figures 5-7, is stable. Stability here means that with increasing n, that is to say when the adaptation is carried out for an infinitely long time, the mean square error produced by the filter 130 reaches a constant value. An algorithm that satisfies this condition is called stable in the root mean square.
  • a change in the velocity parameter ⁇ causes a change in the adaptation precision, ie in the precision, since the coefficients ⁇ i can be adapted to an optimum set of coefficients.
  • a mismatch of the filter coefficients leads to an increase of the average error square or the energy in the difference values ⁇ in the steady state n ⁇ ⁇ .
  • the feedback loop acting on the weights ⁇ i behaves like a low-pass filter whose detection duration constant is inversely proportional to the parameter ⁇ . Consequently, by setting the parameter ⁇ to a small value, the adaptive process is slowed down, with the effects of gradient noise on the weights ⁇ i mostly being filtered out. Conversely, this has the effect of reducing the mismatch.
  • FIG. 8 shows the influence of the setting of the parameter ⁇ on different values ⁇ 1 and ⁇ 2 on the adaptation behavior of the prediction device 16 of FIGS. 5-7 on the basis of a graph in which along the x-axis the number of iterations n and Number of predictions and A-daptions n is plotted and along the y-axis, the average energy of the residual values ⁇ (n) and the mean square error is plotted.
  • a solid line refers to a speed parameter ⁇ 1 .
  • the adaptation to a stationary state in which the average energy of the residual values remains substantially constant requires a number n 1 iterations.
  • the energy of the residual values in the steady state or quasi-stationary state is E 1 .
  • a dashed curve results, where, as can be seen, fewer iterations, namely n 2 , are needed until the steady state is reached, but the steady state is at a higher energy E 2 of the residual values connected is.
  • the steady state at E 1 and E 2 is not characterized by a settling of the mean square of the residual values or Residuals on an asymptotic value, but also by a settling of the filter coefficients ⁇ i with a certain, in the case of ⁇ 1 higher and Case of ⁇ 2 lower, precision to the optimal set of filter coefficients.
  • the velocity parameter ⁇ is first set to the value ⁇ 2 , an adaptation of the coefficients ⁇ i is first achieved more quickly, the change to ⁇ 1 after a certain period of time after the time Reset times then ensures that the adaptation precision for the subsequent period is improved. Overall, this achieves a residual energy curve that allows for higher compression than either parameter setting alone.
  • the present invention is not limited to LMS algorithm implementations.
  • the present invention has been described in more detail as an adaptive prediction algorithm with respect to the LMS algorithm, the present invention is also applicable in the context of other adaptive prediction algorithms where adjustment is via a velocity parameter the vote between adaptation speed on the one hand and adaptation precision on the other hand can be made. Since the adaptation precision in turn has an influence on the energy of the residual values, the speed parameter can always be initially set so that the adaptation speed is high, whereupon it is then set to a value at which the adaptation speed is low but the adaptation precision and thus the energy the residual value is lower. With such prediction algorithms, for example, there would not have to be any connection between the input 120 or the adaptation disturbance 132.
  • further triggering may be performed depending on the degree of adaptation, e.g. a triggering of a speed parameter change when the coefficient cor- responds ⁇ , such as ⁇ . a sum of the absolute values thereof falls below a certain value, indicating an approximation to the quasi-steady state as shown in Fig. 8 except for a certain degree of approach.
  • the inventive scheme can also be implemented in software.
  • the implementation may be on a digital storage medium, in particular a floppy disk or a CD with electronically readable control signals, which can interact with a programmable computer system so that the corresponding method is performed.
  • the invention thus also consists in a computer program product with program code stored on a machine-readable carrier for carrying out the method according to the invention when the computer program product runs on a computer.
  • the invention can thus be realized as a computer program with a program code for carrying out the method when the computer program runs on a computer.

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Claims (25)

  1. Procédé de codage prédictif d'un signal d'information composé d'une succession de valeurs d'information au moyen d'un algorithme de prédiction adaptatif dont les coefficients de prédiction (ωi) peuvent être initialisés, et qui peut être réglé par un paramètre de vitesse (λ), pour fonctionner, au cas où le paramètre de vitesse (λ) présente une première valeur, avec une première vitesse d'adaptation et une première précision d'adaptation et, au cas où le paramètre de vitesse (λ) présente une deuxième valeur, avec une deuxième vitesse d'adaptation, inférieure par rapport à la première, et une deuxième précision d'adaptation, supérieure par rapport à la première, caractérisé par les étapes suivantes consistant à:
    A) initialiser (40) les coefficients de prédiction (ωi);
    B) régler (42) l'algorithme de prédiction adaptatif, pour régler le paramètre de vitesse (λ) à la première valeur;
    C) coder (44) des valeurs d'information successives du signal d'information au moyen de l'algorithme de prédiction adaptatif au paramètre de vitesse (λ) réglé à la première valeur, tant que ne se soit pas écoulée une période prédéterminée après l'étape B), pour coder une première partie du signal d'information;
    D) après écoulement de la période prédéterminée après l'étape B), régler (50) l'algorithme de prédiction adaptatif, pour régler le paramètre de vitesse (λ) à la deuxième valeur; et
    E) coder (44) des valeurs d'information du signal d'information suivant les valeurs d'information codées à l'étape C) au moyen de l'algorithme de prédiction adaptatif au paramètre de vitesse (λ) réglé à la deuxième valeur, pour coder une deuxième partie du signal d'information suivant la première partie.
  2. Procédé selon la revendication 1, dans lequel l'étape C) est effectuée avec adaptation des coefficients de prédiction (ωi) initialisés à l'étape A), pour obtenir des coefficients de prédiction (ωi) adaptés, et dans lequel l'étape E) est effectuée avec adaptation des coefficients de prédiction (ωi) adaptés.
  3. Procédé selon la revendication 1 ou 2, dans lequel les étapes A) à E) sont répétées par intermittence à des moments prédéterminés, pour coder des segments successifs du signal d'information.
  4. Procédé selon la revendication 3, dans lequel les moments prédéterminés reviennent de manière cyclique selon un intervalle de temps prédéterminé.
  5. Procédé selon l'une des revendications précédentes, dans lequel l'étape D) est effectuée après écoulement d'une période prédéterminée après l'étape B).
  6. Procédé selon l'une des revendications précédentes, dans lequel sont obtenues, de l'étape C) et de l'étape E), des différences entre les valeurs d'information du signal d'information et les valeurs prédites qui représentent une version codée du signal d'information.
  7. Dispositif de codage prédictif d'un signal d'information composé d'une succession de valeurs d'information, avec
    un moyen (16, 18) pour exécuter un algorithme de prédiction adaptatif dont les coefficients de prédiction (ωi) peuvent être initialisés, et qui peut être réglé par un paramètre de vitesse (λ), pour fonctionner, au cas où le paramètre de vitesse (λ) présente une première valeur, avec une première vitesse d'adaptation et une première précision d'adaptation et, au cas où le paramètre de vitesse (λ) présente une deuxième valeur, avec une deuxième vitesse d'adaptation, inférieure par rapport à la première, et une deuxième précision d'adaptation, supérieure par rapport à la première, et
    un moyen de réglage (20), couplé au moyen destiné à exécuter l'algorithme de prédiction adaptatif, caractérisé par le fait qu'il contient des moyens qui sont actifs pour provoquer
    A) une initialisation (40) des coefficients de prédiction (ωi);
    B) un réglage (42) de l'algorithme de prédiction adaptatif, pour régler le paramètre de vitesse (λ) à la première valeur;
    un codage (44) de valeurs d'information successives du signal d'information au moyen de l'algorithme de prédiction adaptatif au paramètre de vitesse (λ) réglé à la première valeur, tant que ne se soit pas écoulée une période prédéterminée après l'étape B), pour coder une première partie du signal d'information;
    D) après écoulement de la période prédéterminée après le réglage B), un réglage (50) de l'algorithme de prédiction adaptatif, pour régler le paramètre de vitesse (λ) à la deuxième valeur; et
    E) un codage (44) de valeurs d'information du signal d'information suivant les valeurs d'information codées dans le codage C) au moyen de l'algorithme de prédiction adaptatif au paramètre de vitesse (λ) réglé à la deuxième valeur, pour coder une deuxième partie du signal d'information suivant la première partie.
  8. Dispositif selon la revendication 7, dans lequel le moyen de réglage (20) est réalisé de manière à provoquer que le codage C) s'effectue avec adaptation des coefficients de prédiction (ωi) initialisés en A), pour obtenir des coefficients de prédiction (ωi) adaptés, et que le codage E) s'effectue avec adaptation des coefficients de prédiction (ωi) adaptés.
  9. Dispositif selon l'une des revendications 6 à 8, dans lequel le moyen de réglage (20) est réalisé de manière à provoquer que les étapes A) à E) soient répétées par intermittence à des moments prédéterminés, pour coder des segments successifs du signal d'information.
  10. Dispositif selon la revendication 9, dans lequel le moyen de réglage (20) est réalisé de manière que les moments prédéterminés reviennent de manière cyclique selon un intervalle de temps prédéterminé.
  11. Dispositif selon la revendication 9 ou 10, dans lequel le moyen de réglage (20) est réalisé de manière que l'étape D) soit exécutée après écoulement d'une période déterminée après l'étape B).
  12. Dispositif selon l'une des revendications 7 à 11, dans lequel le moyen destiné à exécuter un algorithme de prédiction adaptatif est réalisé de manière à obtenir des différences entre les valeurs d'nformation du signal d'information et les valeurs prédités qui représentent une version codée du signal d'information.
  13. Procédé de décodage d'un signal d'information codé de manière prédictive composé d'une succession de valeurs de différence au moyen d'un algorithme de prédiction adaptatif dont les coefficients de prédiction (ωi) peuvent être initialisés, et qui peut être réglé par un paramètre de vitesse (λ), pour fonctionner, au cas où le paramètre de vitesse (λ) présente une première valeur, avec une première vitesse d'adaptation et une première précision d'adaptation et, au cas où le paramètre de vitesse (λ) présente une deuxième valeur, avec une deuxième vitesse d'adaptation, inférieure par rapport à la première, et une deuxième précision d'adaptation, supérieure par rapport à la première, caractérisé par les étapes suivantes consistant à:
    F) initialiser (90) les coefficients de prédiction (ωi);
    G) régler (92) l'algorithme de prédiction adaptatif, pour régler le paramètre de vitesse (λ) à la première valeur;
    H) décoder (94) des valeurs de différence successives du signal d'information codé de manière prédictive au moyen de l'algorithme de prédiction adaptatif au paramètre de vitesse (λ) réglé à la première valeur, tant que ne se soit pas écoulée une période prédéterminée après l'étape G), pour décoder une première partie du signal d'information codé de manière prédictive;
    I) après écoulement de la période prédéterminée après l'étape G), régler (100) l'algorithme de prédiction adaptatif, pour régler le paramètre de vitesse (λ) à la deuxième valeur; et
    J) décoder (94) des valeurs de différence du signal d'information codé de manière prédictive suivant les valeurs de différence décodées à l'étape H) au moyen de l'algorithme de prédiction adaptatif au paramètre de vitesse (λ) réglé à la deuxième valeur, pour décoder une deuxième partie du signal d'information codé de manière prédictive.
  14. Procédé selon la revendication 13, dans lequel l'étape H) est effectuée avec adaptation des coefficients de prédiction (ωi) initialisés à l'étape F), pour obtenir des coefficients de prédiction (ωi) adaptés, et dans lequel l'étape J) est effectuée avec adaptation des coefficients de prédiction (ωi) adaptés.
  15. Procédé selon la revendication 13 ou 14, dans lequel les étapes F) à J) sont répétées par intermittence à des moments prédéterminés, pour décoder des segments successifs du signal d'information codé de manière prédictive.
  16. Procédé selon la revendication 15, dans lequel les moments prédéterminés reviennent de manière cyclique selon un intervalle de temps prédéterminé.
  17. Procédé selon l'une des revendications 13 à 16, dans lequel l'étape I) est effectuée après écoulement d'une période prédéterminée après l'étape G).
  18. Procédé selon l'une des revendications 13 à 17, dans lequel les étapes H) à J) comprennent l'addition de différences dans le signal d'information codé de manière prédictive et de valeurs prédites.
  19. Dispositif de décodage d'un signal d'information codé de manière prédictive composé d'une succession de valeurs de différence, avec
    un moyen (16, 18) destiné à exécuter un algorithme de prédiction adaptatif dont les coefficients de prédiction (ωi) peuvent être initialisés, et qui peut être réglé par un paramètre de vitesse (λ), pour fonctionner, au cas où le paramètre de vitesse (λ) présente une première valeur, avec une première vitesse d'adaptation et une première précision d'adaptation et, au cas où le paramètre de vitesse (λ) présente une deuxième valeur, avec une deuxième vitesse d'adaptation, inférieure par rapport à la première, et une deuxième précision d'adaptation, supérieure par rapport à la première, et
    un moyen de réglage (20) qui est couplé au moyen destiné à exécuter l'algorithme de prédiction adaptatif, caractérisé par le fait qu'il contient des moyens qui sont actifs pour provoquer
    F) une initialisation (40) des coefficients de prédiction (ωi);
    G) un réglage (42) de l'algorithme de prédiction adaptatif, pour régler le paramètre de vitesse (λ) à la première valeur;
    H) un décodage (44) de valeurs de différence successives du signal d'information codé de manière prédictive au moyen de l'algorithme de prédiction adaptatif au paramètre de vitesse (λ) réglé à la première valeur, tant que ne se soit pas écoulée une période prédéterminée après le réglage G), pour décoder une première partie du signal d'information codé de manière prédictive;
    I) après écoulement de la période prédéterminée après le réglage G), un réglage (50) de l'algorithme de prédiction adaptatif, pour régler le paramètre de vitesse (λ) à la deuxième valeur; et
    J) un décodage (94) de valeurs de différence du signal d'information codé de manière prédictive suivant les valeurs de différence décodées au décodage H) au moyen de l'algorithme de prédiction adaptatif au paramètre de vitesse (λ) réglé à la deuxième valeur, pour décoder une deuxième partie du signal d'information codé de manière prédictive.
  20. Dispositif selon la revendication 19, dans lequel le dispositif de réglage (20) est réalisé de manière à provoquer que le codage H) s'effectue avec adaptation des coefficients de prédiction (ωi) initialisés en F), pour obtenir des coefficients de prédiction (ωi) adaptés, et que le codage J) s'effectue avec adaptation des coefficients de prédiction (ωi) adaptés.
  21. Dispositif selon la revendication 19 ou 20, dans lequel le moyen de réglage (20) est réalisé de manière à provoquer que les étapes F) à J) soient répétées par intermittence à des moments prédéterminés, pour décoder des segments successifs du signal d'information codé de manière prédictive.
  22. Dispositif selon la revendication 21, dans lequel le moyen de réglage (20) est réalisé de sorte que les moments prédéterminés reviennent de manière cyclique selon un intervalle de temps prédéterminé.
  23. Dispositif selon l'une des revendications 19 à 22, dans lequel le moyen de réglage (20) est réalisé de sorte que l'étape I) soit effectuée après écoulement d'une période prédéterminée après l'étape G).
  24. Dispositif selon l'une des revendications 19 à 23, dans lequel le moyen destiné à exécuter un algorithme de prédiction adaptatif comprend un dispositif destiné à additionner des différences dans le signal d'information codé de manière prédictive et des valeurs prédites.
  25. Programme d'ordinateur avec un code de programme pour mettre en oeuvre le procédé selon l'une des revendications 1 à 6 ou selon l'une des revendications 13 à 18 lorsque le programme d'ordinateur est exécuté sur un ordinateur.
EP04804095A 2004-02-13 2004-12-20 Schema de codage predictif Active EP1700293B1 (fr)

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PCT/EP2004/014496 WO2005083683A1 (fr) 2004-02-13 2004-12-20 Schema de codage predictif

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US11128601B2 (en) * 2007-08-28 2021-09-21 Spencer Health Solutions, Llc Methods, systems, and computer program products for compiling information for use in a command script for a product dispensing system
EP2466580A1 (fr) 2010-12-14 2012-06-20 Fraunhofer-Gesellschaft zur Förderung der Angewandten Forschung e.V. Codeur et procédé de codage prévisionnel, décodeur et procédé de décodage, système et procédé de codage et de décodage prévisionnel et signal d'informations codées prévisionnelles
CN102436215B (zh) * 2011-11-24 2013-06-05 重庆大学 数控冲花打孔机并行控制加工时间虚拟计算方法
JP5994073B2 (ja) * 2013-01-31 2016-09-21 株式会社アクセル 音声信号圧縮装置及び音声信号圧縮方法
ES2710338T3 (es) 2016-05-10 2019-04-24 Von Sobbe Hans Ulrich Sistema de análisis

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IL177124A (en) 2011-04-28
BRPI0418389A (pt) 2007-05-22
NO338722B1 (no) 2016-10-10
RU2006132731A (ru) 2008-03-20
HK1094080A1 (en) 2007-03-16
BRPI0418389B1 (pt) 2019-06-25
RU2345426C2 (ru) 2009-01-27
CN1914670B (zh) 2011-03-23
NO20064021L (no) 2006-09-07
DE102004007185B3 (de) 2005-06-30
KR100852483B1 (ko) 2008-08-18
ES2285551T3 (es) 2007-11-16
EP1700293A1 (fr) 2006-09-13
CA2556024C (fr) 2010-08-10
JP2007534229A (ja) 2007-11-22
US20070016409A1 (en) 2007-01-18
CA2556024A1 (fr) 2005-09-09
JP4351260B2 (ja) 2009-10-28
ATE362169T1 (de) 2007-06-15
CN1914670A (zh) 2007-02-14
KR20070085059A (ko) 2007-08-27
US7386446B2 (en) 2008-06-10
WO2005083683A1 (fr) 2005-09-09
BRPI0418389A8 (pt) 2018-04-03
AU2004316541B2 (en) 2008-04-24
PT1700293E (pt) 2007-08-21
IL177124A0 (en) 2006-12-10
AU2004316541A1 (en) 2005-09-09

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