SSP'05 -- Proceedings

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

Information regarding the paper

Title

A generalized least squares approach to blind separation of sources which have variance dependencies

Author(s)

Shohei Shimizu	Helsinki Institute for Information Technology, Basic Research Unit
Aapo Hyvärinen	Helsinki Institute for Information Technology, Basic Research Unit
Yutaka Kano	Division of Mathematical Science

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Abstract

We discuss the blind source separation problem where the sources are not independent but are dependent only through their variances. Some estimation methods have been proposed on this line. However, most of them require some additional assumptions, a parametric model for their dependencies or a temporal structure of the sources, for example. In this article, we propose a generalized least squares approach to the blind source separation problem in the general case where those additional assumptions do not hold.