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Title:
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A Fast Gradient Approximation for Nonlinear Blind Signal Processing
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Author:
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Solé-Casals, Jordi; Caiafa, Cesar F.
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Other authors:
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Universitat de Vic. Escola Politècnica Superior; Universitat de Vic. Grup de Recerca en Tecnologies Digitals |
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Notes:
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When dealing with nonlinear blind processing algorithms (deconvolution or post-nonlinear source separation), complex mathematical estimations must be done giving as a result very slow algorithms. This is the case, for example, in speech processing, spike signals deconvolution or microarray data analysis. In this paper, we propose a simple method to reduce computational time for the inversion of Wiener systems or the separation of post-nonlinear mixtures, by using a linear approximation in a minimum mutual information algorithm. Simulation results demonstrate that linear spline interpolation is fast and accurate, obtaining very good results (similar to those obtained without approximation) while computational time is dramatically decreased. On the other hand, cubic spline interpolation also obtains similar good results, but due to its intrinsic complexity, the global algorithm is much more slow and hence not useful for our purpose. |
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Subject(s):
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-Tractament del senyal |
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Rights:
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(c) Springer (The original publication is available at www.springerlink.com)
Tots els drets reservats
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Document type:
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Article
info:eu-repo/acceptedVersion |
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Published by:
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Springer
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