Georgiev, P. and Theis, Fabian J. and Cichocki, A.
(2004)
*Blind source separation and sparse component analysis of overcomplete mixtures.*
In:
Proceedings / 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP, May 17 - 21, 2004, Montreal, Quebec, Canada.
IEEE Operations Center, Piscataway, NJ, pp. 493-496.
ISBN 0-7803-8484-9.

Full text not available from this repository.

Other URL: http://homepages.uni-regensburg.de/~thf11669/publications/georgiev04SCA_ICASSP04.pdf

## Abstract

We formulate conditions (k-SCA-conditions) under which we can represent a given (m x N)-matrix X (data set) uniquely (up to scaling and permutation) as a multiplication of (m x n) and (n x N) matrices A and S (often called mixing matrix or dictionary and source matrix, respectively), such that S is sparse of level n-m+k in sense that each column of S has at least n-m+k zero elements. We call this ...

## Export bibliographical data

Item type: | Book section | ||||
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Date: | 2004 | ||||

Institutions: | Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang > Arbeitsgruppe Dr. Fabian Theis | ||||

Projects: | Graduiertenkolleg Nichtlinearität und Nichtgleichgewicht | ||||

Identification Number: |
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Dewey Decimal Classification: | 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 | ||||

Deposited on: | 20 Mar 2007 | ||||

Last modified: | 12 Oct 2010 07:19 | ||||

Item ID: | 1593 |