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An Independent Component Analysis Evolution Based Method for Nonlinear Speech Processing

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Artificial Neural Nets Problem Solving Methods (IWANN 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2687))

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Abstract

This paper proposes a novel Independent Component Analysis algorithm based on the use of genetic algorithms intended for its application to the field of non-linear speech processing. Independent Component Analysis (ICA) is a method for finding underlying factors from multidimensional statistical data, so it can be efficiently applied to suppress interferences and demodulate information in Multilnput-MuliOutput (MIMO) systems.

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Author information

Authors and Affiliations

  1. Dpto. Arquitectura. y Tecnología de Computadores, University of Granada, Spain

    F. Rojas, C. G. Puntonet, I. Rojas & J. Ortega

Authors
  1. F. Rojas
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  2. C. G. Puntonet
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  3. I. Rojas
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  4. J. Ortega
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Editor information

Editors and Affiliations

  1. E.T.S. de Ingeniería Informática Departamento de Inteligencia Artificial, Universidad Nacional de Educación a Distancia, Juan del Rosal, 16, 28040, Madrid, Spain

    José Mira  & José R. Álvarez  & 

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© 2003 Springer-Verlag Berlin Heidelberg

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Rojas, F., Puntonet, C.G., Rojas, I., Ortega, J. (2003). An Independent Component Analysis Evolution Based Method for Nonlinear Speech Processing. In: Mira, J., Álvarez, J.R. (eds) Artificial Neural Nets Problem Solving Methods. IWANN 2003. Lecture Notes in Computer Science, vol 2687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44869-1_86

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  • DOI: https://doi.org/10.1007/3-540-44869-1_86

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40211-4

  • Online ISBN: 978-3-540-44869-3

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