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Regression by topological map: Application on real data

  • Oral Presentations: Applications Scientific Applications I
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Artificial Neural Networks — ICANN 96 (ICANN 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1112))

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Abstract

We address the problem of oceanographic data regression with constrainted Kohonen self-organizing maps. Using constrainted topological mapping algorithm on real data, we show that it is well suited to geographic needs. It appears as an elegant way to overcome uneven spatial sampling problems.

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References

  1. Najafi Cherkasski. Constrainted topological mapping for nonparametric regression analysis. Neural Network, 4:27–40, 1991.

    Google Scholar 

  2. Hardle. Applied Nonparametric Regression. Cambridge University Press, Cambridge, 1990.

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  3. Hardle. Smoothing techniques with implementation in S. Springer-Verlag, New York, 1991.

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  4. Kohonen. Self-organisation and associative memory. Springer-Verlag, 3rd edition, 1995.

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  5. Schulten Ritter, Martinetz. Neural Computation and Self-Organizing Maps, An Introduction. Addison-Wesley Publishing Company, 1992.

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Authors and Affiliations

  1. CEDRIC, Conservatoire National des Arts et Métiers, 292 rue Saint Martin, 75003, Paris, France

    Ph. Daigremont, F. Badran & S. Thiria

  2. Laboratoire d'Océanographie et de Climatologie (LODYC), Université de Paris VI, 4 place Jussieu, T14, 75005, Paris, France

    S. Thiria

  3. Laboratoire ARPEGES, CNRS URA 1757, Observatoire de Paris-Meudon, 92195, Meudon cedex, France

    H. de Lassus

Authors
  1. Ph. Daigremont
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  2. H. de Lassus
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  3. F. Badran
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  4. S. Thiria
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Editor information

Christoph von der Malsburg Werner von Seelen Jan C. Vorbrüggen Bernhard Sendhoff

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© 1996 Springer-Verlag Berlin Heidelberg

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Daigremont, P., de Lassus, H., Badran, F., Thiria, S. (1996). Regression by topological map: Application on real data. In: von der Malsburg, C., von Seelen, W., Vorbrüggen, J.C., Sendhoff, B. (eds) Artificial Neural Networks — ICANN 96. ICANN 1996. Lecture Notes in Computer Science, vol 1112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61510-5_34

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  • DOI: https://doi.org/10.1007/3-540-61510-5_34

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61510-1

  • Online ISBN: 978-3-540-68684-2

  • eBook Packages: Springer Book Archive

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