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Wavelet frames based estimator

  • Part III: Learning: Theory and Algorithms
  • Conference paper
  • First Online:
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

This paper introduces a new wavelet frames-based functional estimation method (i.e. a wavelet-based neural network which works for more than one dimension functions. The use of frames and wavelets in our approach yields to robust decomposition with an interesting parsimonious property: compression of information in few coefficients. This approach is illustrated using the problem of estimating radioactivity in Chernobyl area.

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Author information

Authors and Affiliations

  1. Heuristique & Diagnostic des Système Complexes, U.M.R. C.N.R.S., 6599, France

    Skander Soltani, Stephane Canu & Yves Grandvalet

  2. Division de Mathématiques Appliquées, Université de Technologie de Compiegne, B.P. 20529, 60205, Compiegne Cedex, France

    Daniel Boichu

Authors
  1. Skander Soltani
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  2. Stephane Canu
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  3. Daniel Boichu
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  4. Yves Grandvalet
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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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Soltani, S., Canu, S., Boichu, D., Grandvalet, Y. (1997). Wavelet frames based estimator. 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/BFb0020174

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  • DOI: https://doi.org/10.1007/BFb0020174

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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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