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Spline Neural Networks for Blind Separation of Post-Nonlinear-Linear Mixtures.
- Source :
-
IEEE Transactions on Circuits & Systems. Part I: Regular Papers . Apr2004, Vol. 51 Issue 4, p817-829. 13p. - Publication Year :
- 2004
-
Abstract
- In this paper, a novel paradigm for blind source separation in the presence of nonlinear mixtures is presented. In particular, the paper addresses the problem of post-nonlinear mixing followed by another instantaneous mixing system. This model is called here the post-nonlinear-linear model. The method is based on the use of the recently introduced flexible activation function whose control points are adaptively changed: a neural model based on adaptive B-spline functions is employed. The signal separation is achieved through an information maximization criterion. Experimental results and comparison with existing solutions confirm the effectiveness of the proposed architecture. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15498328
- Volume :
- 51
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Circuits & Systems. Part I: Regular Papers
- Publication Type :
- Periodical
- Accession number :
- 12949200
- Full Text :
- https://doi.org/10.1109/TCSI.2004.826210