Local convergence analysis of FastICA

Authors:
Hao Shen;Knut Hüper
Affiliations:
Department of Information Engineering, Research School of Information Sciences and Engineering, The Australian National University, Canberra, ACT, Australia;Department of Information Engineering, Research School of Information Sciences and Engineering, The Australian National University, Canberra, ACT, Australia
Venue:
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Year:
2006

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Abstract

The FastICA algorithm can be considered as a selfmap on a manifold. It turns out that FastICA is a scalar shifted version of an algorithm recently proposed. We put these algorithms into a dynamical system framework. The local convergence properties are investigated subject to an ideal ICA model. The analysis is very similar to the wellknown case in numerical linear algebra when studying power iterations versus Rayleigh quotient iteration.