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An Evolutionary Approach for Blind Inversion of Wiener Systems

An Evolutionary Approach for Blind Inversion of Wiener Systems
 
Rojas, Fernando ; Solé-Casals, Jordi ; Puntonet, Carlos G.
2007

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Enllaç permanent: http://hdl.handle.net/10854/2851
 
Versió de l'editor: https://doi.org/10.1007/978-3-540-74494-8_33
 

Abstract

The problem of blind inversion of Wiener systems can be considered as a special case of blind separation of post-nonlinear instantaneous mixtures. In this paper, we present an approach for nonlinear deconvolution of one signal using a genetic algorithm. The recovering of the original signal is achieved by trying to maximize ...»»»»
The problem of blind inversion of Wiener systems can be considered as a special case of blind separation of post-nonlinear instantaneous mixtures. In this paper, we present an approach for nonlinear deconvolution of one signal using a genetic algorithm. The recovering of the original signal is achieved by trying to maximize an estimation of mutual information based on higher order statistics. Analyzing the experimental results, the use of genetic algorithms is appropriate when the number of samples of the convolved signal is low, where other gradient-like methods may fail because of poor estimation of statistics.^^^^

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Conference object

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(c) Springer (The original publication is available at www.springerlink.com)
 
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Citation:

Rojas, F., Sole-Casals, J., & Puntonet, C. G. (2007). An evolutionary approach for blind inversion of wiener systems. Lecture Notes in Computer Science Volume 4666, 2007, pp 260-267