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。
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.
出处
《电信科学》
北大核心
2012年第5期43-48,共6页
Telecommunications Science
基金
国家自然科学基金资助项目(No.51179074)
关键词
人工蜂群
盲源抽取
目标函数
超高斯分布
亚高斯分布
artificial bee colony, blind source extraction, goal function, super-gaussian distribution, sub-gaussian distribution
