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A Genetic Algorithm for Constructing Wavelet Neural Networks

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Intelligent Computing (ICIC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4113))

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Abstract

In this paper, a new algorithm is proposed for the design of WNNs. The design is performed in an evolutionary way, which allowed us to construct a parsimonious model to satisfy the design requirement. A genetic algorithm (GA) is used to select a wavelet basis, and the fitness of a wavelet is evaluated according to the residue reduction. Output weights are updated using least square techniques. Simulations demonstrate the effectiveness of the proposed algorithm.

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Author information

Authors and Affiliations

  1. Department of Computer Science, East China Normal University,  

    Jinhua Xu

Authors
  1. Jinhua Xu
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Editor information

Editors and Affiliations

  1. Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China

    De-Shuang Huang

  2. Carnegie Mellon University,  

    Kang Li

  3. School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Stranmillis Road, BT9 5AH, Belfast, UK

    George William Irwin

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© 2006 Springer-Verlag Berlin Heidelberg

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Xu, J. (2006). A Genetic Algorithm for Constructing Wavelet Neural Networks. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing. ICIC 2006. Lecture Notes in Computer Science, vol 4113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816157_29

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  • DOI: https://doi.org/10.1007/11816157_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-37271-4

  • Online ISBN: 978-3-540-37273-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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