Model structure selection in convolutive mixtures

Authors:
Mads Dyrholm;Scott Makeig;Lars Kai Hansen
Affiliations:
Informatics and Mathematical Modelling, Technical University of Denmark, Lyngby, Denmark;Swartz Center for Computational Neuroscience, University of California, San Diego 0961, La Jolla, CA;Informatics and Mathematical Modelling, Technical University of Denmark, Lyngby, Denmark
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 CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious representation in many practical mixtures. The new filter-CICAAR allows Bayesian model selection and can help answer questions like: ’Are we actually dealing with a convolutive mixture?’. We try to answer this question for EEG data.