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Lookup NU author(s): Dr Wai Lok Woo, Emeritus Professor Satnam Dlay
A nonlinear approach based on the Tikhonov regularised cost function is presented for blind signal separation of nonlinear mixtures. The proposed approach uses a multilayer perceptron as the nonlinear demixer and combines both information theoretic learning and structural complexity learning into a single framework. It is shown that this approach can be jointly used to extract independent components while constraining the overall perceptron network to be as sparse as possible. The update algorithm for the nonlinear demixer is subsequently derived using the new cost function. Sparseness in the network connection is utilised to determine the total number of layers required in the multilayer perceptron and to prevent the nonlinear demixer from outputting arbitrary independent components. Experiments are meticulously conducted to study the performance of the new approach and the outcomes of these studies are critically assessed for performance comparison with existing methods. © IEE, 2005.
Author(s): Woo WL, Dlay SS
Publication type: Article
Publication status: Published
Journal: IEE Proceedings: Vision, Image and Signal Processing
Year: 2005
Volume: 152
Issue: 1
Pages: 61-73
Print publication date: 01/02/2005
ISSN (print): 1350-245X
ISSN (electronic): 1359-7108
Publisher: The Institution of Engineering and Technology
URL: http://dx.doi.org/10.1049/ip-vis:20051190
DOI: 10.1049/ip-vis:20051190
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