一种基于时域的欠定盲源分离方法

摘要

提出一种基于时域的欠定盲源分离方法,该方法首先根据非平稳信号的特性,采用一种基于差分峰度的欠定盲抽取算法逐次分离欠定下的非平稳信号,然后利用二阶统计量的抽取算法分离剩余的源信号。仿真实验结果表明了该方法不仅能同时分离服从超高斯分布和亚高斯分布的源信号,且它比其他传统的方法具有更优越的估计性能。%The sources extraction from their underdetermined instantaneous mixtures via timedomain is presented in this article.Firstly,an algorithm based on differential kurtosis to separate non-stationary sources with underdetermined case one by one is introduced.Then the rest sources are recovered by using an algorithm based on second-order statistics.The simulation results show that the proposed method can separate sources of super-and sub-Gaussian distribution,and its superior performances to other conventional methods.