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IWANN
2001
Springer

The Minimum Entropy and Cumulants Based Contrast Functions for Blind Source Extraction

14 years 4 months ago
The Minimum Entropy and Cumulants Based Contrast Functions for Blind Source Extraction
Abstract. In this paper we address the problem of blind source extraction of a subset of “interesting” independent sources from a linear convolutive or instantaneous mixture. The interesting sources are those which are independent and, in a certain sense, are sparse and far away from Gaussianity. We show that in the low-noise limit and when none of the desired sources is Gaussian, the minimum entropy and cumulants based approaches can solve the problem. These criteria, with roots in Blind Deconvolution and in Projection Pursuit, will be proposed here for the simultaneous blind extraction of a group of independent sources. Then, we suggest simple algorithms which, working on the Stiefel manifold perform maximization of the proposed contrast functions.
Sergio Cruces, Andrzej Cichocki, Shun-ichi Amari
Added 30 Jul 2010
Updated 30 Jul 2010
Type Conference
Year 2001
Where IWANN
Authors Sergio Cruces, Andrzej Cichocki, Shun-ichi Amari
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