Georgiev, P. and Theis, Fabian and Cichocki, A. (2005) Sparse component analysis and blind source separation of underdetermined mixtures. IEEE TRANSACTIONS ON NEURAL NETWORKS, 16 (4). pp. 992-996. ISSN 1045-9227, 1941-0093
Full text not available from this repository. (Request a copy)Abstract
In this letter, we solve the problem of identifying matrices S is an element of R-n x N and A is an element of R-m x n knowing only their multiplication X = AS, under some conditions, expressed either in terms of A and sparsity of S (identifiability conditions), or in terms of X (sparse component analysis (SCA) conditions). We present algorithms for such identification and illustrate them by examples.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | ; blind source separation (BSS); sparse component analysis (SCA); underdetermined mixtures |
| Subjects: | 500 Science > 570 Life sciences |
| Divisions: | Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 07 May 2021 08:21 |
| Last Modified: | 07 May 2021 08:21 |
| URI: | https://pred.uni-regensburg.de/id/eprint/35936 |
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