Blind source separation of overdetermined linear-quadratic mixtures

Authors:
Leonardo T. Duarte;Ricardo Suyama;Romis Attux;Yannick Deville;João M. T. Romano;Christian Jutten
Affiliations:
DSPCom Lab, Universtity of Campinas, Campinas, Brazil;Enginnering Modeling and Applied Social Sciences, UFABC, Santo André, Brazil;DSPCom Lab, Universtity of Campinas, Campinas, Brazil;LATT, Université de Toulouse, CNRS, Toulouse, France;DSPCom Lab, Universtity of Campinas, Campinas, Brazil;GIPSA-Lab, CNRS UMR, Grenoble and Institut Universitaire de France
Venue:
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
Year:
2010

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Abstract

This work deals with the problem of source separation in overdetermined linear-quadratic (LQ) models. Although the mixing model in this situation can be inverted by linear structures, we show that some simple independent component analysis (ICA) strategies that are often employed in the linear case cannot be used with the studied model. Motivated by this fact, we consider the more complex yet more robust ICA framework based on the minimization of the mutual information. Special attention is given to the development of a solution that be as robust as possible to suboptimal convergences. This is achieved by defining a method composed of a global optimization step followed by a local search procedure. Simulations confirm the effectiveness of the proposal.