SSP'05 -- Proceedings

	IEEE/SP 13th workshop on Statistical Signal Processing July, 17-20, 2005 - Bordeaux - France

Information regarding the paper

Title

Non-negative Source Separation using the Maximum Likelihood Approach

Author(s)

Saïd Moussaoui	UHP Nancy 1, CRAN, CRAN, UMR 7039 CNRS-UHP-INPL
David Brie	UHP Nancy 1, CRAN, CRAN, UMR 7039 CNRS-UHP-INPL
Cédric Carteret	UHP Nancy 1, LCPME, UMR 7564 UHP-CNRS

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Abstract

This papers addresses the problem of non-negative source separation using the maximum likelihood approach. It is shown that this approach can be effective by considering that the sources are distributed according to a density having a non-negative support from which an adequate non-linear separating function can be derived. In the particular of spectroscopic data which is our main concern, a good candidate is the Gamma distribution which allows to encode both non-negativity and sparsity of the source signals. Numerical experiments are used to assess the performances of the method.