The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Un algorithme rapide pour accélérer le processus de recherche de codage par quantification vectorielle est présenté. En utilisant la somme et les normes partielles d'un vecteur, des inégalités éliminatoires sont construites. Tout d'abord, l'inégalité basée sur la somme est utilisée pour déterminer les limites du mot de code candidat à la recherche. Ensuite, en utilisant une inégalité basée sur la norme du sous-vecteur et une autre inégalité combinant la distance partielle avec la norme du sous-vecteur, davantage de mots de code inutiles sont éliminés sans le calcul complet de la distance. L'algorithme proposé peut rejeter un grand nombre de mots de code, tout en n'introduisant aucune distorsion supplémentaire par rapport à l'algorithme de recherche complète conventionnel. Les résultats expérimentaux montrent que l'algorithme proposé surpasse les algorithmes de recherche de pointe existants en réduisant la complexité informatique et le nombre de calculs de distorsion.
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ShanXue CHEN, FangWei LI, WeiLe ZHU, TianQi ZHANG, "Fast Searching Algorithm for Vector Quantization Based on Subvector Technique" in IEICE TRANSACTIONS on Information,
vol. E91-D, no. 7, pp. 2035-2040, July 2008, doi: 10.1093/ietisy/e91-d.7.2035.
Abstract: A fast algorithm to speed up the search process of vector quantization encoding is presented. Using the sum and the partial norms of a vector, some eliminating inequalities are constructeded. First the inequality based on the sum is used for determining the bounds of searching candidate codeword. Then, using an inequality based on subvector norm and another inequality combining the partial distance with subvector norm, more unnecessary codewords are eliminated without the full distance calculation. The proposed algorithm can reject a lot of codewords, while introducing no extra distortion compared to the conventional full search algorithm. Experimental results show that the proposed algorithm outperforms the existing state-of-the-art search algorithms in reducing the computational complexity and the number of distortion calculation.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e91-d.7.2035/_p
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@ARTICLE{e91-d_7_2035,
author={ShanXue CHEN, FangWei LI, WeiLe ZHU, TianQi ZHANG, },
journal={IEICE TRANSACTIONS on Information},
title={Fast Searching Algorithm for Vector Quantization Based on Subvector Technique},
year={2008},
volume={E91-D},
number={7},
pages={2035-2040},
abstract={A fast algorithm to speed up the search process of vector quantization encoding is presented. Using the sum and the partial norms of a vector, some eliminating inequalities are constructeded. First the inequality based on the sum is used for determining the bounds of searching candidate codeword. Then, using an inequality based on subvector norm and another inequality combining the partial distance with subvector norm, more unnecessary codewords are eliminated without the full distance calculation. The proposed algorithm can reject a lot of codewords, while introducing no extra distortion compared to the conventional full search algorithm. Experimental results show that the proposed algorithm outperforms the existing state-of-the-art search algorithms in reducing the computational complexity and the number of distortion calculation.},
keywords={},
doi={10.1093/ietisy/e91-d.7.2035},
ISSN={1745-1361},
month={July},}
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TY - JOUR
TI - Fast Searching Algorithm for Vector Quantization Based on Subvector Technique
T2 - IEICE TRANSACTIONS on Information
SP - 2035
EP - 2040
AU - ShanXue CHEN
AU - FangWei LI
AU - WeiLe ZHU
AU - TianQi ZHANG
PY - 2008
DO - 10.1093/ietisy/e91-d.7.2035
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E91-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2008
AB - A fast algorithm to speed up the search process of vector quantization encoding is presented. Using the sum and the partial norms of a vector, some eliminating inequalities are constructeded. First the inequality based on the sum is used for determining the bounds of searching candidate codeword. Then, using an inequality based on subvector norm and another inequality combining the partial distance with subvector norm, more unnecessary codewords are eliminated without the full distance calculation. The proposed algorithm can reject a lot of codewords, while introducing no extra distortion compared to the conventional full search algorithm. Experimental results show that the proposed algorithm outperforms the existing state-of-the-art search algorithms in reducing the computational complexity and the number of distortion calculation.
ER -