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独立分量分析对相关信号源的盲辨识性能分析
引用本文:王刚,胡德文. 独立分量分析对相关信号源的盲辨识性能分析[J]. 计算机工程与应用, 2005, 41(4): 23-25,174
作者姓名:王刚  胡德文
作者单位:国防科技大学机电工程与自动化学院,长沙,410073;国防科技大学机电工程与自动化学院,长沙,410073
基金项目:国家杰出青年科学基金(编号:60225015),高等学校优秀青年教师教学科研奖励计划资助
摘    要:源信号之间统计独立是经典独立分量分析模型的基本要求。对实际信号而言,严格的统计独立是很难满足的,统计独立通常解释为尽可能的独立或者物理独立。在探讨了源信号之间存在弱线性相关后,对源信号的构成依次做出了三种假设,分析了独立分量分析对相关信号源的辨识能力。理论研究和实验表明,即使信号源之间存在弱相关性,独立分量分析方法仍然反映信号源的波形特征。

关 键 词:独立分量分析  盲辨识  盲源分离
文章编号:1002-8331-(2005)04-0023-03

Blind Identification Ability of Independent Component Analysis when Sources are Correlated
Wang Gang,Hu Dewen. Blind Identification Ability of Independent Component Analysis when Sources are Correlated[J]. Computer Engineering and Applications, 2005, 41(4): 23-25,174
Authors:Wang Gang  Hu Dewen
Abstract:Statistical independence is an important and basic restriction in the classical model of Independent Component Analysis(ICA).However,the assumption cannot be severely satisfied in real environment and practically the requirement often can only be interpreted as independent as possible or physical independent.This paper addresses the blind identification ability of ICA when sources are not independent but somewhat correlated.Three assumptions are made in series and the corresponding analyses are given on the correlation of independent components and correlated sources.The results show the idealistic blind identification ability of ICA,and the robust restoration ability of wave-performing.The performance is also demonstrated in the experiments.
Keywords:Independent Component Analysis(ICA)  blind identification  Blind Source Separation(BSS)  
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