Skip to main content
Springer Nature Link
Log in

Separation of Convolutive Mixtures with Hybrid Sources

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

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

  • 3364 Accesses

Abstract

We propose in this paper a unique method to separate sources that may have different statistical properties, in the case of FIR convolutive mixtures. No constraint is necessary on the source statistics (i.i.d variables, Gaussian sources or temporally correlated sources..), nor on the number of each type of sources. On the contrary of previous works, no assumption of overdetermined mixtures is used. It relies on joint block-diagonalization of correlation matrices of some appropriate variables called differential complex signals, which are introduced in the paper.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Comon, P.: Contrasts for multichannel blind deconvolution. IEEE Signal Processing Letters 3(7), 209–211 (1996)

    Article  Google Scholar 

  2. Simon, C., Loubaton, P., Jutten, C.: Separation of a class of convolutive mixtures: a contrast function approach. Signal Processing 81, 883–887 (2001)

    Article  MATH  Google Scholar 

  3. Thomas, J., Deville, Y., Hossseini, S.: Time –Domain Fast Fixed-Point Algorithms for Convolutive ICA. IEEE Signal Processing Letters 13(4), 228–231 (2006)

    Article  Google Scholar 

  4. Tugnait, J.K.: Identification and deconvolution of multichannel linear non-Gaussian processes using HOS and inverse filter criteria. IEEE T. SP 45(3), 658–672

    Google Scholar 

  5. Ghorokhov, A., Loubaton, P.: Subspace based techniques for second order blind separation of convolutive mixtures with temporally correlated sources. IEEE Trans. Circuit Syst. 44(9), 813–820 (1997)

    Article  Google Scholar 

  6. Bousbiah, H., Belouchrani, A., Abed-Meraim, K.: Jacobi-like algorithm for blind signal separation of convolutive mixtures. Electronic Letters 37, 1049–1050 (2001)

    Article  Google Scholar 

  7. Févotte, C., Doncarli, C.: A unified presentation of blind source separation methods for convolutive mixtures using block-diagonalization. In: ICA 2003, Nara, Japan (2003)

    Google Scholar 

  8. Ghennioui, H., Fadaili, E., Thirion, N., Adib, A., Moreau, E.: A Nonunitary Joint Block Diagonalization Algorithm for Blind Separation of Convolutive Mixtures of Sources. IEEE Signal Processing Letters 14(11) (November 2007)

    Google Scholar 

  9. Deville, Y., Benali, M., Abrad, F.: Differential source separation for underdetermined instantaneous or convolutive mixtures. Signal Processing 84(10)

    Google Scholar 

  10. Choi, Cichocki, A., Deville, Y.: Differential decorrelation for nonstationary source separation. In: ICA 2001, Helsinki (2001)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. GIPSA-Lab, ENSIEG, BP 46, 38402, Saint-Martin d’Hères, France

    Christine Servière

Authors
  1. Christine Servière
    View author publications

    You can also search for this author in PubMed Google Scholar

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

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Servière, C. (2009). Separation of Convolutive Mixtures with Hybrid Sources. 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_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-00599-2_15

  • 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)

Publish with us

Policies and ethics