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Lookup NU author(s): Dr Wai Lok Woo, Dr Sadettin Sali
A new technique is presented for instantaneous blind signal separation from nonlinear mixtures using a general neural network based demixer scheme. The nonlinear demixer model follows directly from the general mixer model. In the first part of the paper a general mixer model is described which includes linear mixtures as a special case. In the second part the general framework for a demixer based on a feedforward multilayer perceptron (FMLP) employing a class of continuously differentiable nonlinear functions is presented. A detailed derivation of the learning algorithm used to adapt the demixer's parameters is given. Cost functions based on both maximum entropy (ME) and minimum mutual information (MMI) have been studied. The performance of the new technique was investigated using various experiments derived from the general mixer model and using real-time data. These studies illustrated the superiority and the generality of the new technique compared with existing methods.
Author(s): Woo WL, Sali S
Publication type: Article
Publication status: Published
Journal: IEE Proceedings: Vision, Image and Signal Processing
Year: 2002
Volume: 149
Issue: 5
Pages: 253-262
ISSN (print): 1350-245X
ISSN (electronic): 1359-7108
Publisher: IEEE
URL: http://dx.doi.org/10.1049/ip-vis:20020548
DOI: 10.1049/ip-vis:20020548
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