Independent component analysis based on symmetrised scatter matrices

Authors:
S. Taskinen;S. Sirkiä;H. Oja
Affiliations:
Department of Mathematics and Statistics, University of Jyväskylä, Finland;Department of Mathematics and Statistics, University of Jyväskylä, Finland;Tampere School of Public Health, University of Tampere, Finland
Venue:
Computational Statistics & Data Analysis
Year:
2007

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Abstract

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.