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Wavelet De-noising for Blind Source Separation in Noisy Mixtures

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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

Blind source separation, which supposes that the sources are independent, is a well known domain in signal processing. However, in a noisy environment the estimation of the criterion is harder due to the noise. In strong noisy mixtures, we propose two new principles based on the combination of wavelet de-noising processing and blind source separation. We compare them in the cases of white/correlated Gaussian noise.

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References

  1. Hérault, J., Jutten, C., Ans, B.: Détection de grandeurs primitives dans un message composite par une architecture de calcul neuromimétrique en apprentissage non supervisé. In: Gretsi, Nice, France, May 1985, vol. 2, pp. 1017–1020 (1985)

    Google Scholar 

  2. Jutten, C., Taleb, A.: Source separation: from dusk till dawn. In: Independent compoment analysis 2000, Helsinki, Finlande, June 2000, pp. 15–26 (2000)

    Google Scholar 

  3. Amari, S.I., Cichocki, A.: Adaptive Blind Signal and Image Processing, Learning Algorithms and Applications. Wiley, Chichester (2002)

    Google Scholar 

  4. Hyvärinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. Wiley, Chichester (2001)

    Book  Google Scholar 

  5. Paraschiv-Ionescu, A., Jutten, C., Aminian, K., et al.: Source separation in strong noisy mixtures: a study of wavelet de-noising pre-processing. In: ICASSP 2002, Orlando, Floride (2002)

    Google Scholar 

  6. Mallat, S.: A wavelet tour of signal processing, 2nd edn. Academic Press, London (1999)

    MATH  Google Scholar 

  7. Yang, H.H., Amari, S.I., Cichocki, A.: Information-theoric approach to blind separation of sources in non-linear mixture. Signal Processing 64(3), 291–300 (1998)

    Article  Google Scholar 

  8. Coifman, R.R., Donoho, D.L.: Translation-invariant de-noising. In: Wavelets and statistics. Springer lecture notes in Statistics, vol. 103, pp. 125–150. Springer, New York

    Google Scholar 

  9. De Lathauwer, L., Callaerts, D., De Moor, B., et al.: Fetal electrocardiogram extraction by source subspace separation. In: Proc. IEEE Workshop on HOS, Girona, Spain, June 12-14, pp. 134–138 (1995)

    Google Scholar 

  10. Rivet, B., Jutten, C., Vigneron, V.: Wavelet de-noising for blind source separation in noisy mixtures. Technical report, Technical report for the BLInd Source Separation project (BLISS IST 1999-14190) (2003)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Institut National Polytechnique de Grenoble, Laboratoire des Images et des Signaux, Grenoble, France

    Bertrand Rivet, Vincent Vigneron & Christian Jutten

  2. Swiss Federal Institute of Technology, Lausanne, Switzerland

    Anisoara Paraschiv-Ionescu

Authors
  1. Bertrand Rivet
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  2. Vincent Vigneron
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  3. Anisoara Paraschiv-Ionescu
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  4. Christian Jutten
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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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Rivet, B., Vigneron, V., Paraschiv-Ionescu, A., Jutten, C. (2004). Wavelet De-noising for Blind Source Separation in Noisy Mixtures. 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_34

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  • DOI: https://doi.org/10.1007/978-3-540-30110-3_34

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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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