Blind separation of sparse sources using jeffrey’s inverse prior and the EM algorithm

Authors:
Cédric Févotte;Simon J. Godsill
Affiliations:
Engineering Dept., University of Cambridge, Cambridge, UK;Engineering Dept., University of Cambridge, Cambridge, UK
Venue:
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Year:
2006

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Abstract

In this paper we study the properties of the Jeffrey’s inverse prior for blind separation of sparse sources. This very sparse prior was previously used for Wavelet-based image denoising. In this paper we consider separation of 3 × 3 and 2 × 3 noisy mixtures of audio signals, decomposed on a MDCT basis. The hierarchical formulation of the inverse prior allows for EM-based computation of MAP estimates. This procedure happens to be fast when compared to a standard more complex Markov chain Monte Carlo method using the flexible Student t prior, with competitive results obtained.