Übersetzung für "Predictive coding" in Deutsch

Thus, predictive coding would have to take place in the time range here.

Such motion vectors can be used for example in predictive coding methods such as MPEG-2 or H263.

This type of predictive coding of spectral values thus is referred to as TNS or temporal noise shaping technique.

Linear predictive coding rather realistically models natural generation of a speech signal by a human being.

Frames are encoded, for example, using predictive coding, also know as inter-frame coding.

Within the context of linear predictive coding analysis, the fundamental frequency value is determined as one signal parameter of typically several signal parameters.

Determining the instantaneous fundamental frequency value may be performed within the context of a linear predictive coding analysis (LPC).

For this reason the method described herein can also be adopted in decoding methods which conduct a predictive coding.

The paper "Adaptive Predictive Speech Coding Based on Pitch-Controlled Interruption/Reiteration Techniques" by A. Frei et al., published in the Proceedings of the IEEE, 1973, International Conference on Communications, pp. 46-12 through 46-16, discloses a method in which, for the transmission of voiced portions of a speech signal, only one pitch period is transmitted as delta-coded signal, and in which this signal section of variable length is stored in the receiver in a shift register and is repeated several times for obtaining the output signal.

The TNS technique (TNS=Temporal Noise Shaping), generally speaking, permits temporal shaping of the fine structure of quantization noise by means of predictive coding of the spectral values.

This means in fact that the series of spectral coefficients in relation to frequency is stationary, and this is why predictive coding techniques can be used in efficient manner for representing this signal by utilizing a common set of prediction coefficients.

This signal can be coded best and in the most efficient manner in the time range, since only the temporal position as well as the power of the Dirac pulse need to be transmitted, which by consequent application of dualism leads to the result that predictive coding in the frequency range also constitutes a suitable method for efficient coding.

It is very important not to confuse predictive coding of spectral coefficients in relation to frequency with the known dual concept of prediction of spectral coefficients from one block to the next one, which is already implemented and also described in the afore-mentioned article (M. Bosi, K. Brandenburg, S. Quakenbush, L. Fielder, K. Akagiri, H. Fuchs, M. Diets, J. Herre, G. Davidson, Yoshiaki Oikawa: “ISO/IEC MPEG-2 Advanced Audio Coding”, 101st AES Convention, Los Angeles 1996, Preprint 4382).

Predictive coding techniques, in consideration of the duality between time and frequency range, can be treated substantially analogous to the already known prediction from one spectral coefficient to the spectral coefficient of the same frequency in the next block.

The filter parameters can be LPC (Linear Predictive Coding) coefficients, LTP (Long Term Prediction) indices or LTP (Long Term Prediction) amplitude factors.

Usually, in the case of so-called predictive coding methods, that is to say in the case of coding methods in which a so-called motion estimation is carried out, the present picture information is estimated from already transmitted picture information from picture areas and only a so-called estimation error produced as a result of the motion estimation is communicated.

To assess the signal segments, the audio discriminator 3 uses, for example, LPC (linear predictive coding) transformation, with which the coefficients of an adaptive filter corresponding to the human voice spectrum are calculated.

Our experienced discovery and technology professionals use predictive coding and other proven data reduction strategies including filtering, de-duplication, and early case assessment to minimise processing and review costs.

The invention of the "linear predictive coding LPC" by Prof. Schroeder and Bishnu Atal in 1967 and their invention of the "codebook exited linear prediction CELP" ist the most important fundament for today`s speech compression algorithms.

One focus of the department within this topic is audio coding, specifically with a very low end-to-end delay, e.g. for communication applications and - for this purpose - necessary signal processing algorithms, such as low-delay filter banks and predictive coding.

The lecture will discuss the basic coding techniques entropy coding, quantization, predictive coding, transformation coding, which are the main components of modern image and video codecs.

Therefore, the coefficient calculation module 36 performs, for example, LPC (LPC=linear predictive coding) analysis per block of the prefiltered signal for obtaining the prediction coefficients.

For someone performing the manual change, it is no problem to mark the corresponding word in a graphically represented signal wave form and to subject said signal portion to linear predictive coding with a modified fundamental frequency if said person knows the corresponding language (German, English, Chinese, Japanese, etc.) and has basic knowledge in audio signal processing.