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International Conference on Independent Component Analysis and Signal Separation

ICA 2004: Independent Component Analysis and Blind Signal Separation pp 358–365Cite as

A Novel Method to Recover N Sources from N-1 Observations and Its Application to Digital Communications

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

Abstract

This paper deals with the blind source separation (BSS) problem with fewer sensors than sources. We propose a simple procedure to transform the problem with N sources and N–1 observations in a classical BSS problem with N observations which can be solved using many well-known algorithms. We will also show how to apply this idea to digital communications for separating BPSK and QPSK signals.

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References

  1. Abrard, F., Deville, Y., White, P.: From blind source separation to blind source cancellation in the undetermined case: a new approach base on time-frequency analysis. In: Proc. ICA 2001, San Diego, USA, December 2001, pp. 734–739 (2001)

    Google Scholar 

  2. Cao, X.-R., Liu, R.-W.: General approach to blind source separation. IEEE Trans. Signal Processing 44(3), 562–571 (1996)

    Article  Google Scholar 

  3. Cardoso, J.F., Souloumiac, A.: Blind Beamforming for non-Gaussian Signals. IEE-Proceedings-F 140(6), 362–370 (1993)

    Google Scholar 

  4. Cardoso, J.F., Laheld, B.: Equivariant adaptive source separation. IEEE Trans. on Signal Processing 44(2), 3017–3030 (1996)

    Article  Google Scholar 

  5. Cardoso, J.F.: Blind signal separation: statistical principles. Proc. IEEE 86(10), 225–254 (1998)

    Article  Google Scholar 

  6. Cichochi, A., Amari, S.I.: Adaptive blind signal and image processing. Learning algorithms and applications. Wiley, England (2002)

    Google Scholar 

  7. Comon, P., Grellier, O.: Non-linear inversion of undetermined mixtures. In: Proc. ICA 1999, Aussois, France, January 1999, pp. 461–465 (1999)

    Google Scholar 

  8. Diamantaras, K.I., Chassioti, E.: Blind separation of N binary sources from one observation: a deterministic approach. In: Proc. ICA 2000, Helsinki, Finland, June 2000, pp. 93–98 (2000)

    Google Scholar 

  9. Jourjune, A., Rickard, S., Yilmaz, O.: Blind separation of disjoint orthogonal signals: demixing N sources from 2 mixtures. In: Proc. ICASSP 2000, Istanbul, Turkey, June 2000, pp. 2985–2988 (2000)

    Google Scholar 

  10. Taleb, A., Jutten, C.: On undetermined source separation. In: Proc. ICASSP 1999, Arizona, March 1999, pp. 1445–1448 (1999)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Departamento de Electrónica e Sistemas, Universidade da Coruña, Campus de Elviña s/n, 15.071, A Coruña, Spain

    Adriana Dapena

Authors
  1. Adriana Dapena
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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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Dapena, A. (2004). A Novel Method to Recover N Sources from N-1 Observations and Its Application to Digital Communications. 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_46

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  • DOI: https://doi.org/10.1007/978-3-540-30110-3_46

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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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