Model structure selection in convolutive mixtures

Mads Dyrholm, Scott Makeig, Lars Kai Hansen

AbstractThe 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 parsimoneous
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.
Keywordsica convolutive maximum likelihood contextual eeg model selection
TypeConference paper [With referee]
Conference6th International Conference on Independent Component Analysis and Blind Source Separation
Year2006
Electronic version(s)[pdf]
BibTeX data [bibtex]
IMM Group(s)Intelligent Signal Processing


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