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Geometric Overcomplete ICA

Theis, Fabian J. and Lang, Elmar (2002) Geometric Overcomplete ICA. In: Verleysen, Michel, (ed.) Proceedings / 10th European Symposium on Artificial Neural Networks, ESANN'2002: Bruges, Belgium, April 24 - 25 - 26, 2002. d-side, Evere, Belgium, pp. 217-223. ISBN 2-930307-02-1.

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Other URL: http://homepages.uni-regensburg.de/~thf11669/publications/theis02overcomplete_ESANN02.pdf


In independent component analysis (ICA), given some signal input the goal is to find an independent decomposition. We present an algorithm based on geometric considerations to decompose a linear mixture of more sources than sensor signals. We present an efficient method for the matrix-recovery step in the framework of a two-step approach to the source separation problem. The second step - sourcerecovery - uses the standard maximum-likelihood approach.

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Item type:Book section
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
Projects:Graduiertenkolleg Nichtlinearität und Nichtgleichgewicht
Dewey Decimal Classification:500 Science > 530 Physics
500 Science > 570 Life sciences
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Yes
Item ID:1556
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