Puntonet, C. G. and Mansour, A. and Bauer, C. and Lang, E. (2002) Separation of sources using simulated annealing and competitive learning. NEUROCOMPUTING, 49 (1-4). pp. 39-60. ISSN 0925-2312
Full text not available from this repository.Abstract
This paper presents a new adaptive procedure for, the linear and non-linear separation of signals with non-uniform, symmetrical probability distributions, based on both simulated annealing and competitive learning methods by means of a neural network, considering the properties of the vectorial spaces of sources and mixtures, and using a multiple, linearization in the mixture space. The main characteristics of the method are its simplicity and the rapid convergence experimentally validated by the separation of many kinds of signals, such as speech or biomedical data. (C) 2002 Elsevier Science B.V. All rights reserved.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | BLIND SEPARATION; GEOMETRIC-PROPERTIES; NONLINEAR MIXTURES; ALGORITHM; blind separation; independent component analysis; simulated annealing; competitive learning; neural networks |
| Subjects: | 500 Science > 530 Physics 500 Science > 570 Life sciences |
| Divisions: | Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 25 Aug 2021 12:25 |
| Last Modified: | 25 Aug 2021 12:25 |
| URI: | https://pred.uni-regensburg.de/id/eprint/39637 |
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