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
벡터 양자화 인코딩의 검색 속도를 높이는 빠른 알고리즘이 제시됩니다. 벡터의 합과 부분 노름을 사용하여 일부 제거 부등식을 구성합니다. 먼저 합에 따른 부등식을 사용하여 검색 후보 코드워드의 범위를 결정합니다. 그런 다음 하위 벡터 놈을 기반으로 한 부등식과 부분 거리를 하위 벡터 놈과 결합한 또 다른 부등식을 사용하여 전체 거리 계산 없이 더 불필요한 코드워드가 제거됩니다. 제안하는 알고리즘은 기존 완전탐색 알고리즘에 비해 추가적인 왜곡이 발생하지 않으면서도 많은 수의 코드워드를 거부할 수 있다. 실험 결과, 제안하는 알고리즘이 기존의 최신 검색 알고리즘에 비해 계산 복잡도와 왜곡 계산 횟수를 줄이는 데 우수한 성능을 보이는 것으로 나타났다.
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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},}
부
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 -