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矢量量化的遗传k-均值算法
Genetic k-means Algorithm for Vector Quantization
【摘要】 提出了一种遗传k-均值算法,该算法通过改进标准遗传操作及采用可变变异率,使 其在矢量量化应用中表现出很好的性能。实验证明,该算法能够获得质量高于k-均值和模糊 k-均值算法的矢量量化码书,为设计全局最优码书提供了新思路。
【Abstract】 A genetic k-means algorithm for vector quantization is proposed in t his paper. By using k-means algorithm as a novel genetic crossover operator, thi s algorithm shows superior performance for image vector quantization in comparis on with k-means and fuzzy k-means algorithms. Also, a variable mutation rate is demonstrated to be helpful for improving the algorithm performance. This hybrid algorithm gives an idea to the combination of GA and conventional technologies f or solving more complex problem.
- 【文献出处】 计算机工程 ,Computer Engineering , 编辑部邮箱 ,2003年21期
- 【分类号】TP18
- 【被引频次】8
- 【下载频次】179