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Neural network based processing for smart sensors arrays

  • Part IV: Signal Processing: Blind Source Separation, Vector Quantization, and Self-Organization
  • Conference paper
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Artificial Neural Networks — ICANN'97 (ICANN 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1327))

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Abstract

Source separation (SS) algorithm is an attractive approach for designing smart sensor array, able to increase spatial selectivity and to cancel spurious sources. The source number being unknown and able to vary, a pre-processing algorithm is developped in this paper for providing estimation of the source number before source separation. On-line source separation is then achieved in the above time variant context.

Ch. Jutten is professor at ISTG of Univ. Joseph Fourier of Grenoble. This project is partly supported by ELESA in cooperation with A. Chovet and A. lonescu of LPCS.

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Authors and Affiliations

  1. INPG-TIRF, 46 avenue Félix Viallet, 38031, Grenoble Cedex, France

    A. Paraschiv-Ionescu, C. Jutten & G. Bouvier

Authors
  1. A. Paraschiv-Ionescu
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  2. C. Jutten
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  3. G. Bouvier
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Editor information

Wulfram Gerstner Alain Germond Martin Hasler Jean-Daniel Nicoud

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© 1997 Springer-Verlag Berlin Heidelberg

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Paraschiv-Ionescu, A., Jutten, C., Bouvier, G. (1997). Neural network based processing for smart sensors arrays. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020214

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  • DOI: https://doi.org/10.1007/BFb0020214

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63631-1

  • Online ISBN: 978-3-540-69620-9

  • eBook Packages: Springer Book Archive

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