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Neural-Network Based Physical Fields Modeling Techniques

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Computer Science – Theory and Applications (CSR 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3967))

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Abstract

The possibility of solving elliptic and parabolic partial differential equations by using cellular neural networks with specific structure is investigated. The method of solving varialble coefficients parabolic PDEs is proposed. Issues of cellular neural network stability are examined.

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References

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Author information

Authors and Affiliations

  1. Belgorod Shukhov State Technological University, Russia

    Konstantin Bournayev

Authors
  1. Konstantin Bournayev
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Editor information

Editors and Affiliations

  1. IRMAR, Université de Rennes, Campus de Beaulieu, 35042, Rennes Cedex, France

    Dima Grigoriev

  2. Intel Corporation, JF1-13, 2111 NE 25th Avenue, 97124, Hillsboro, OR, USA

    John Harrison

  3. Steklov Institute of Mathematics at St. Petersburg, 27 Fontanka, St., 191023, Petersburg, Russia

    Edward A. Hirsch

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© 2006 Springer-Verlag Berlin Heidelberg

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Bournayev, K. (2006). Neural-Network Based Physical Fields Modeling Techniques. In: Grigoriev, D., Harrison, J., Hirsch, E.A. (eds) Computer Science – Theory and Applications. CSR 2006. Lecture Notes in Computer Science, vol 3967. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11753728_40

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  • DOI: https://doi.org/10.1007/11753728_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34166-6

  • Online ISBN: 978-3-540-34168-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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