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Interpolation Mechanism of Functional Networks

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Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005 (ICANN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3697))

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Abstract

In this paper, the interpolation mechanism of functional networks is discussed. And a kind of three layers Functional networks with single input unit and single output unit and four layers functional networks with double input units and single output unit is designed, a learning algorithm for function approximation is based on minimizing a sum of squares with a unique minimum has been proposed, which can respectively approximate a given one-variable continuous function and a given two-variable continuous function satisfying given precision. Finally, several given examples show that the interpolation method is effective and practical.

This work was supported by NSF of China.

An erratum to this chapter can be found at http://dx.doi.org/10.1007/11550907_163 .

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Author information

Authors and Affiliations

  1. Institute for Intelligence Information Processing, Xidian University, Xi’ an, Shanxi, 710071, China

    Yong-Quan Zhou & Li-Cheng Jiao

  2. College of Computer and Information Science, Guangxi University for Nationalities, Nanning, Guangxi, 530006, China

    Yong-Quan Zhou

Authors
  1. Yong-Quan Zhou
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  2. Li-Cheng Jiao
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Editor information

Editors and Affiliations

  1. Department of Informatics, Nicolaus Copernicus University, Toruń, Poland

    Włodzisław Duch

  2. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01–447, Warsaw, Poland

    Janusz Kacprzyk

  3. Adaptive Informatics Research Centre, Helsinki University of Technology, P.O. Box 5400, 02015, HUT, Finland

    Erkki Oja

  4. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Sławomir Zadrożny

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© 2005 Springer-Verlag Berlin Heidelberg

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Zhou, YQ., Jiao, LC. (2005). Interpolation Mechanism of Functional Networks. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3697. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550907_8

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  • DOI: https://doi.org/10.1007/11550907_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28755-1

  • Online ISBN: 978-3-540-28756-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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