Exterior penalty function method based ICA algorithm for hybrid sources using GKNN estimation
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
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In this paper, a new adaptive non-linear function for blind signal separation is presented. It is based on a spline approximation whose control points are adaptively changed using information maximization techniques. The monotonously increasing characteristic is obtained using suitable B-spline functions imposing simple constraints on its control points. In particular, the problem of adaptively maximizing the entropy of the output is considered in the context of blind separation of independent sources. We derive a simple form of the learning algorithm, which allows not only adapting the separation matrix coefficients but also the shape of the non-linear functions. A comparison with the Mixture-Of-Densities approach is also presented on some experimental data that demonstrates the effectiveness and efficiency of the proposed method.