电信科学

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一种基于人工蜂群优化的有序盲源抽取方法

王荣杰,周海峰,詹宜巨   

  1. 集美大学轮机工程学院 中山大学工学院;集美大学轮机工程学院;中山大学工学院
  • 出版日期:2012-05-15 发布日期:2012-05-15
  • 基金资助:
    国家自然科学基金资助项目(No.51179074)

A Bind Source Extraction Method with the Order Based on Artificial Bee Colony Optimization

Wang Rongjie,Zhou Haifeng and Zhan Yiju   

  1. Marine Engineering Institute, Jimei University School of Engineering, Sun Yat-sen University;Marine Engineering Institute, Jimei University;School of Engineering, Sun Yat-sen University
  • Online:2012-05-15 Published:2012-05-15

摘要: 提出了一种基于人工蜂群优化的盲源抽取方法,该方法首先根据源信号的高阶统计特性构造了用于估计分离向量的目标函数,然后通过人工蜂群算法优化其函数获得最佳分离向量,并达到逐次恢复源信号的目的。仿真实验结果表明,该方法不仅能依4阶累积量绝对值降序地实现源信号的盲分离,还能同时分离服从亚高斯分布的图像信号和超高斯分布的语音信号。

Abstract: To separate source signals one by one, we consider the blind source extraction problem of instantaneous mixtures using artificial bee colony optimization algorithm. A goal function is constructed first by exploiting the higher statistics prosperities of source signals, then the optimal extracted vectors are determined through maximizing the goal function using artificial bee colony optimization algorithm, so as to separate source one by one. The simulation results show that the method can achieve the blind separation for mixed signals in decreasing order of absolute kurtosis. Moreover, it can separate images of sub-gaussian distribution and speeches of super-gaussian distribution.

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