基于遗传算法的矢量量化
VQ BASED ON GENETIC ALGORITHM
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摘要: 本文提出了一种基于遗传算法的矢量化方法。矢量量化码书设计本质是搜索训练矢量的最佳分类。遗传算法有卓越的全局优化搜索能力,易搜索到全局最优的矢量分类,形成高度优化的码书,可克服传统方法局部优化的缺陷。该算法不依赖初始条件、鲁棒性好、结构规则、并行性高。Abstract: A new vector quantization(VQ) approach based on genetic algorithm(GA) is presented in this paper. VQ codebook design is essentially a classification of training vectors. Because of GA s global optimum ability, using GA for codebook training can obstain a global optimum codebook, and overcome local optimum limitation of traditional algorithms. This method is also independent on initial conditions, more robust, highly regular and parallel in architecture.
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Linde Y,et al. An algorithm for vector quantizer design. IEEE Trans. on comm., 1980, COM 28(l): 84-95.[2]Laregetto F, et al. Unbalanced tree structure frame adaptive vector quantization of image se[3]quences.SPIE,1990.1224: 281-304.[4][3][5]Holland J H. Adaptation in Nature and Artificial Systems.The University of Michigan Press, 1975. -
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