Nonlinear Blind Source Separation Using Hybrid Neural Networks
نویسندگان
چکیده
This paper proposes a novel algorithm based on minimizing mutual information for a special case of nonlinear blind source separation: postnonlinear blind source separation. A network composed of a set of radial basis function (RBF) networks, a set of multilayer perceptron and a linear network is used as a demixing system to separate sources in post-nonlinear mixtures. The experimental results show that our proposed method is effective, and they also show that the local character of the RBF network’s units allows a significant speedup in the training of the system.
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تاریخ انتشار 2006