Theis, Fabian J. and Puntonet, Carlos G. and Lang, Elmar W. (2006) Median-based clustering for underdetermined blind signal processing. IEEE SIGNAL PROCESSING LETTERS, 13 (2). pp. 96-99. ISSN 1070-9908, 1558-2361
Full text not available from this repository. (Request a copy)Abstract
In underdetermined blind source separation, more sources are to be extracted from less observed mixtures without knowing both sources and mixing matrix. k-means-style clustering algorithms are commonly used to do this algorithmically given sufficiently sparse sources, but in any case other than deterministic sources, this lacks theoretical justification. After establishing that mean-based algorithms converge to wrong solutions in practice, we propose a median-based clustering scheme. Theoretical justification as well as algorithmic realizations (both online and batch) are given and illustrated by some examples.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | SOURCE SEPARATION; LINEAR ICA; ALGORITHM; blind source separation (BSS); independent component analysis (ICA) |
| Subjects: | 500 Science > 570 Life sciences |
| Divisions: | Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang > Arbeitsgruppe Dr. Fabian Theis |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 24 Feb 2021 07:20 |
| Last Modified: | 24 Feb 2021 07:20 |
| URI: | https://pred.uni-regensburg.de/id/eprint/34987 |
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