Independent component analysis based on symmetrised scatter matrices

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• 作者：S. Taskinen ; S. Sirkiä ; ; H. Oja
• 关键词：Affine equivariance ; FastICA ; Independence property ; Source separation ; Symmetrised scatter matrix
• 刊名：Computational Statistics and Data Analysis
• 出版年：2007
• 期刊代码：19_01679473
• 类别：cp
• 出版时间：15 June 2007
• 卷：51
• 期：10
• 页码：5103-5111
• 文件大小：468 K

摘要

A new method for separating the mixtures of independent sources has been proposed recently in [Oja et al. (2006). Scatter matrices and independent component analysis. Austrian J. Statist., to appear]. This method is based on two scatter matrices with the so-called independence property. The corresponding method is now further examined. Simple simulation studies are used to compare the performance of so-called symmetrised scatter matrices in solving the independence component analysis problem. The results are also compared with the classical FastICA method. Finally, the theory is illustrated by some examples.