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New Eigensystem-Based Method for Blind Source Separation

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Independent Component Analysis and Blind Signal Separation (ICA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3195))

Abstract

In this paper, it is presented an algorithm to construct a cumulant matrix that has a well-separated extremal eigenvalue. The corresponding eigenvector is well-conditioned and could be used to develop robust algorithms for blind source extraction. Simulations demonstrate the effectiveness of the proposed approach.

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Author information

Authors and Affiliations

  1. Área de Teoría de la Señal y Comunicaciones, Universidad de Sevilla, Avda. de los Descubrimientos s/n, 41092, Sevilla, Spain

    Rubén Martín-Clemente, Susana Hornillo-Mellado & José I. Acha

  2. Departamento de Arquitectura y Tecnología de Computadores, Universidad de Granada, E-18071, Granada, Spain

    Carlos G. Puntonet

Authors
  1. Rubén Martín-Clemente
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  2. Susana Hornillo-Mellado
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  3. Carlos G. Puntonet
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  4. José I. Acha
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Editor information

Editors and Affiliations

  1. Dept. of Architecture and Computer Technology, University of Granada, Spain

    Carlos G. Puntonet  & Alberto Prieto  & 

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© 2004 Springer-Verlag Berlin Heidelberg

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Martín-Clemente, R., Hornillo-Mellado, S., Puntonet, C.G., Acha, J.I. (2004). New Eigensystem-Based Method for Blind Source Separation. In: Puntonet, C.G., Prieto, A. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2004. Lecture Notes in Computer Science, vol 3195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30110-3_5

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  • DOI: https://doi.org/10.1007/978-3-540-30110-3_5

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23056-4

  • Online ISBN: 978-3-540-30110-3

  • eBook Packages: Springer Book Archive

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