Examples of using Vector quantization in English and their translations into French
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Vector quantization.
The method uses a vector quantization with preclassification.
Vector Quantization Applications.
In the first part,we focus on greedy vector quantization.
Vector Quantization of the Second ISP Subvector.
Other techniques such as vector quantization can however be used.
As a variant, the block 43 can be configured to perform differential vector quantization.
The method uses a vector quantization procedure on n bits, with for example n=5.
Abstract: Fast search algorithms for image coding vector quantization are proposed.
Vector quantization of the last seven LSP(once per frame)(in functional unit 85 in FIG. 8);
FIG. 2 the functional diagram of the vector quantization of the voicing information.
A vector quantization of the voicing configurations is shown in a table referenced 22 in FIG. 6.
The method notably calls upon a procedure of vector quantization with classification.
Vector Quantization(VQ) can provide high compression ratios based on relatively simple structures.
The present invention relates to a process for the vector quantization of low bit rate vocoders.
Vector quantization bits GR of four residual gains concerning the four segments of the windows respectively;
The spectral content of the sub-bands is thereafter coded by spherical vector quantization(block 307.
Each coding modulus CSn(1≦n≦N) operates vector quantization of the signal Sn which is submitted to it.
Self-organizing neural models have already been studied,especially for vector quantization tasks.
These modules CE 0 m operate by vector quantization in the same way as the modules CEn described previously.
The spectral content of each of the sub-bands is retrieved by inverse spherical vector quantization(block 403.
TOTAL= words The abbreviation VQ corresponds to vector quantization andMSVQ multi-stage vector quantization procedure.
To improve the compression efficiency, colors andpositions may use a vector quantization.
FIG. 4 is a diagram showing the construction of vector quantization libraries used in the processes according to the invention;
One solution to this problem of dimensionality is the use of constrained VQ such as network vector quantization(LVQ.
It is applied where data compression or vector quantization is an issue, for example speech recognition, image processing or pattern recognition.
FIG. 2 illustrates the partitioning of the space of the possible vector states(transformed image blocks) by vector quantization.
According to the principle of vector quantization, the choice of the representative is made by minimizing the mean distortion over the vectors of the cell.
Encoding/decoding of digital signals,especially in vector quantization with permutation codes.
It uses vector quantization(VQ) technology to compress hyperspectral datacubes and then applies algorithms to extract the information directly from the compressed data.