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Separability of Convolutive Mixtures: Application to the Separation of Combustion Noise and Piston-Slap in Diesel Engine

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Independent Component Analysis and Blind Signal Separation (ICA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3889))

Abstract

We focus on convolutive mixtures, expressed in time-domain. Separation is known to be obtained by testing the independence between delayed outputs. This criterion can be much simplified and we prove in this paper that testing the independence between the contributions of all sources on the same sensor at same time index also leads to separability. We recover the contribution by using Wiener filtering (or Minimal Distorsion Principal) which is included in the separation filters. The independence is tested here with the mutual information. It is minimized only for non-delayed outputs of the Wiener filters. The test is easier and shows good results on simulation and experimental signals for the separation of piston slap and combustion in diesel engine.

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References

  1. Yellin, D., Weinstein, E.: Criteria for multichannel signal separation. IEEE Trans. on Signal Processing, 2158–2168 (August 1994)

    Google Scholar 

  2. Papoulis, A.: Probability, random variables and stochastic processes. McGraw-Hill, New York (1991)

    Google Scholar 

  3. Babaie-Zadeh, M., Jutten, C.: Mutual information minimization: application to blind source separation. Signal Processing 85(5), 975–995 (2005)

    Article  MATH  Google Scholar 

  4. El Rahbi, M., Gelle, G., Fenniri, H., Delaunay, G.: A penalized mutual information criterion for blind separation of convolutive mixtures. Signal Processing 84(4), 1979–1984

    Google Scholar 

  5. Matsuoka, K., Ohba, Y., Toyota, Y., Nakashima, S.: Blind separation for convolutive mixtures of many voices. In: Int. workshop on acoustic echo and noise control, Kyoto, Japan (September 2003)

    Google Scholar 

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

    Article  Google Scholar 

  7. Comon, P.: Independent component analysis, a new concept. IEEE Trans. on Signal Processing 36(3), 287–314 (1994)

    MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Laboratoire des Images et des Signaux, ENSIEG, BP 46, 38402, Saint-Martin d’Hères, France

    Moussa Akil & Christine Servière

Authors
  1. Moussa Akil
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  2. Christine Servière
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Editor information

Editors and Affiliations

  1. Siemens Corporate Research, 755 College Road East, 08540, Princeton, NJ, USA

    Justinian Rosca

  2. Department of CSEE, Oregon Health and Science University, Portland, Oregon, USA

    Deniz Erdogmus

  3. Dep. of Electrical and Computer Engineering, University of Florida, Gainesville, Florida, USA

    José C. Príncipe

  4. McMaster University, 1280 Main Street West, L8S 4K1, Hamilton, Ontario, Canada

    Simon Haykin

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© 2006 Springer-Verlag Berlin Heidelberg

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Akil, M., Servière, C. (2006). Separability of Convolutive Mixtures: Application to the Separation of Combustion Noise and Piston-Slap in Diesel Engine. In: Rosca, J., Erdogmus, D., Príncipe, J.C., Haykin, S. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2006. Lecture Notes in Computer Science, vol 3889. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11679363_40

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  • DOI: https://doi.org/10.1007/11679363_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-32630-4

  • Online ISBN: 978-3-540-32631-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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