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Blind Separation of Cyclostationary Signals

  • Conference paper
Independent Component Analysis and Signal Separation (ICA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5441))

Abstract

In this paper, we propose a new method for the blind source separation with assuming that the source signals are cyclostationarity. The proposed method exploits the characteristics of cyclostationary signals in the Fraction-of-Time probability framework in order to simultaneously separate all sources without restricting the distribution or the number of cycle frequencies of each source. Furthermore, a new identifiability condition is also provided to show which kind of cyclostationary source can be separated by the second-order cyclostationarity statistics. Numerical simulations are presented to demonstrate the effectiveness of the proposed approach.

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Author information

Authors and Affiliations

  1. LASPI EA3059, University of Saint Etienne, Jean Monnet, France

    Nhat Anh Cheviet, Mohamed El Badaoui & Francois Guillet

  2. Elec. Eng. Dept., Ecole Nationale Polytechnique, Algiers, Algeria

    Adel Belouchrani

Authors
  1. Nhat Anh Cheviet
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  2. Mohamed El Badaoui
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  3. Adel Belouchrani
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  4. Francois Guillet
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Electrical Engineering, ITE 324, University of Maryland, Baltimore County, 1000 Hilltop Circle, MD 21250, Baltimore, USA

    Tülay Adali

  2. Domaine Universitaire, GIPSA-lab, BP 46, 38402, Saint Martin d’Hères Cedex, France

    Christian Jutten

  3. Departamento de Microonda e Óptica (DMO), FEEC / Unicamp, Avenida Albert Einstein 400, 13083-852, Campinas, Sao Paulo, Brazil

    João Marcos Travassos Romano

  4. Centro Tecnológico, Curso de Engenharia Elétrica, Universidade Federal do Maranhão, Avenida dos Portugueses, s/n, Bacanga, 65080-040, São Luís, MA, Brazil

    Allan Kardec Barros

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© 2009 Springer-Verlag Berlin Heidelberg

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Cheviet, N.A., El Badaoui, M., Belouchrani, A., Guillet, F. (2009). Blind Separation of Cyclostationary Signals. In: Adali, T., Jutten, C., Romano, J.M.T., Barros, A.K. (eds) Independent Component Analysis and Signal Separation. ICA 2009. Lecture Notes in Computer Science, vol 5441. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00599-2_4

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  • DOI: https://doi.org/10.1007/978-3-642-00599-2_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00598-5

  • Online ISBN: 978-3-642-00599-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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