Deutsch
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
Abstract
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.
| Item Type: | Book Section |
|---|---|
| Institutions: | Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang |
| Projects: | Graduiertenkolleg Nichtlinearität und Nichtgleichgewicht |
| Subjects: | 500 Science > 530 Physics 500 Science > 570 Life sciences |
| Status: | Published |
| Refereed: | Yes, this version has been refereed |
| Created at the University of Regensburg: | Yes |
| Owner: | Redakteur Physik |
| Deposited On: | 20 Mar 2007 |
| Last Modified: | 15 Oct 2010 09:42 |
| Item ID: | 1556 |
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