| 基于遗传算法的矢量量化 |
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| 引用本文： | 涂承杰,郭立,朱琛.基于遗传算法的矢量量化[J].电子与信息学报,1998,20(4):562-565. |
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| 作者姓名： | 涂承杰 郭立 朱琛 |
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| 作者单位： | 中国科学技术大学电子技术部，中国科学技术大学电子技术部，中国科学技术大学电子技术部 合肥 230026，合肥 230026，合肥 230026 |
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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。
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| 关 键 词： | 矢量量化 遗传算法 适应度函数 分类 |
| 收稿时间： | 1997-1-29 |
| 修稿时间： | 1997-8-27 |
VQ BASED ON GENETIC ALGORITHM |
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| Tu Chengjie,Guo Li,Zhu Chen.VQ BASED ON GENETIC ALGORITHM[J].Journal of Electronics & Information Technology,1998,20(4):562-565. |
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| Authors: | Tu Chengjie Guo Li Zhu Chen |
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| Affiliation: | Electronic Engineering Department USTC Hefei 230026 |
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| 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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| Keywords: | Vector quantization Genetic algorithm Fitness function Classification |
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