基于Pearson系统模型的盲信号分离研究  

RESEARCH ON BLIND SOURCE SEPARATION BASED ON PEARSON SYSTEM MODEL

作　　者：蒋慧钧[1] 王耀明[1] 王沛[1] 

机构地区：[1]上海师范大学数理信息学院,上海200234

出　　处：《计算机应用与软件》2007年第4期150-151,188,共3页Computer Applications and Software

摘　　要：独立分量分析是盲源分离的主流技术。自然梯度算法是其中非常重要的算法之一。介绍一种最大似然框架下的Pear-son系统模型。该方法的优点是无须知晓信号的概率分布,实验结果表明,该算法能有效地分离随机混合的信号,特别对于非对称源有比同类算法更理想的效果。Independent component analysis is a mainstream technique for blind source separation. Natural gradient algorithm is one of the most important algorithms. This paper introduces a method for blind source separation without any knowledge of their probability distributions. This is achieved under a maximum likelihood framework by Pearson system model. Simulation result shows that the proposed algorithm is able to separate random mixing signals, especially for asymmetric sources.

关 键 词：盲信源分离 自然梯度算法 Pearson系统模型 评价函数 

分 类 号：TN911.7[电子电信—通信与信息系统]