Referenced Items are not available for this document.
A new non-information-theoretic approach is described for the blind source separation (BSS) problem. It is based on an auto-encoder neural network which incorporates a pruning algorithm. Hidden units are nonlinear, and ones that survive the pruning become the source extractors. As such, no assumption is needed for the number of sources. Simulation results show that the auto-encoder can make BSS for a broad class of source-signal mixtures without changing the nonlinear activation function of the hidden units
Published in:
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
(Volume:2
)
Date of Conference: 2002
- Page(s):
- 1305 - 1309
- Meeting Date :
- 12 May 2002-17 May 2002
- ISSN :
- 1098-7576
- Print ISBN:
- 0-7803-7278-6
- INSPEC Accession Number:
- 7328443
- Conference Location :
- Honolulu, HI
- Digital Object Identifier :
- 10.1109/IJCNN.2002.1007683
- Product Type:
- Conference Publications
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