【摘要】 独立分量分析(ICA)是近期发展起来的一种统计学方法,旨在寻求对非高斯分布数据进行有效的表示,使得各个分量在统计学上独立,或者尽最大可能地独立。文章介绍了独立分量分析的发展过程,基本理论等。许多应用中,这种表示意在获取数据的基本结构,包括特征提取和信号分离,目前主要应用在盲源分离,特征提取,盲反卷积等方面。更多还原

【Abstract】 Independent component analysis(ICA) is recently developed as a kind of statistical methods,Sought to express the data of non-gaussian distribution effectively,made different components were independent or as much as possible to independence in statistics.This paper introduced the development of process of independent component analysis,basic theory,and so on.In many applications,this expression aimed to obtain the basic structure of data,including feature extraction and signal separation,at present,the main application in blind source separation,feature extraction,blind deconvolution,etc.更多还原