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Overcomplete ICA with a Geometric Algorithm

Theis, Fabian J. ; Lang, Elmar ; Westenhuber, Tobias ; Puntonet, Carlos G.



Abstract

We present an independent component analysis (ICA) algorithm based on geometric considerations [10] [11] to decompose a linear mixture of more sources than sensor signals. Bofill and Zibulevsky [2] recently proposed a two-step approach for the separation: first learn the mixing matrix, then recover the sources using a maximum-likelihood approach. We present an efficient method for the ...

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