A High Efficent Memetic Algorithm for theDesign of Vector Quantization

碩士 === 清雲科技大學 === 電子工程所 === 99 === A novel memetic algorithm (MA) for the design of vector quantizers (VQs) is presented in this paper. The algorithm uses steady-state genetic algorithm (SSGA) for the global search and C-Means algorithm for the local improvement. As compared with the usual MA using...

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Bibliographic Details
Main Authors:	Zong-Cheng Li, 李宗晟
Other Authors:	歐謙敏
Format:	Others
Language:	zh-TW
Published:	2011
Online Access:	http://ndltd.ncl.edu.tw/handle/43582554180045392075

id	ndltd-TW-099CYU05428010
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spelling	ndltd-TW-099CYU054280102015-10-19T04:03:36Z http://ndltd.ncl.edu.tw/handle/43582554180045392075 A High Efficent Memetic Algorithm for theDesign of Vector Quantization 一種高效能改良式基因演算法之向量量化器設計 Zong-Cheng Li 李宗晟碩士清雲科技大學電子工程所 99 A novel memetic algorithm (MA) for the design of vector quantizers (VQs) is presented in this paper. The algorithm uses steady-state genetic algorithm (SSGA) for the global search and C-Means algorithm for the local improvement. As compared with the usual MA using the generational GA for global search, the proposed MA effectively reduces the computational time for VQ training. In addition, it attains near global optimal solution, and its performance is insensitive to the selection of initial codewords. Numerical results show that the proposed algorithm has significantly lower CPU time over other MA counterparts running on the same genetic population size for VQ design. 歐謙敏 2011 學位論文 ; thesis 40 zh-TW
collection	NDLTD
language	zh-TW
format	Others
sources	NDLTD
description	碩士 === 清雲科技大學 === 電子工程所 === 99 === A novel memetic algorithm (MA) for the design of vector quantizers (VQs) is presented in this paper. The algorithm uses steady-state genetic algorithm (SSGA) for the global search and C-Means algorithm for the local improvement. As compared with the usual MA using the generational GA for global search, the proposed MA effectively reduces the computational time for VQ training. In addition, it attains near global optimal solution, and its performance is insensitive to the selection of initial codewords. Numerical results show that the proposed algorithm has significantly lower CPU time over other MA counterparts running on the same genetic population size for VQ design.
author2	歐謙敏
author_facet	歐謙敏 Zong-Cheng Li 李宗晟
author	Zong-Cheng Li 李宗晟
spellingShingle	Zong-Cheng Li 李宗晟 A High Efficent Memetic Algorithm for theDesign of Vector Quantization
author_sort	Zong-Cheng Li
title	A High Efficent Memetic Algorithm for theDesign of Vector Quantization
title_short	A High Efficent Memetic Algorithm for theDesign of Vector Quantization
title_full	A High Efficent Memetic Algorithm for theDesign of Vector Quantization
title_fullStr	A High Efficent Memetic Algorithm for theDesign of Vector Quantization
title_full_unstemmed	A High Efficent Memetic Algorithm for theDesign of Vector Quantization
title_sort	high efficent memetic algorithm for thedesign of vector quantization
publishDate	2011
url	http://ndltd.ncl.edu.tw/handle/43582554180045392075
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A High Efficent Memetic Algorithm for theDesign of Vector Quantization

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