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Characterization of the Sources in Convolutive Mixtures: A Cumulant-Based Approach

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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

This paper addresses the characterization of independent and non-Gaussian sources in a linear mixture. We present an eigensystem based approach to determine the number of independent components in the signal received by a single sensor. The temporal structure of the sources is also characterized using fourth-order statistics.

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Author information

Authors and Affiliations

  1. Área de Teoría de la Señal y Comunicaciones, Universidad de Sevilla, Spain

    Susana Hornillo-Mellado & Rubén Martín-Clemente

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

    Carlos G. Puntonet & Manuel Rodríguez-Álvarez

  3. Dpto. Ing. Sist. y Auto., Tecn. Electrónica y Electrónica, Univ. de Cádiz, Spain

    Juan Manuel Górriz

Authors
  1. Susana Hornillo-Mellado
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  2. Carlos G. Puntonet
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  3. Rubén Martín-Clemente
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  4. Manuel Rodríguez-Álvarez
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  5. Juan Manuel Górriz
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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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Hornillo-Mellado, S., Puntonet, C.G., Martín-Clemente, R., Rodríguez-Álvarez, M., Górriz, J.M. (2004). Characterization of the Sources in Convolutive Mixtures: A Cumulant-Based Approach. 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_75

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  • DOI: https://doi.org/10.1007/978-3-540-30110-3_75

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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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