• DocumentCode
    2025383
  • Title

    Structure optimization of wavelet neural network using rough set theory

  • Author

    Li, Yiguo ; Shen, Jiong ; Lu, Zhenzhong

  • Author_Institution
    Dept. of Power Eng., Southeast Univ., Nanjing, China
  • Volume
    1
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    652
  • Abstract
    This paper presents an approach to minimize the redundancy of structure existing in frame-based wavelet neural networks using the rough sets theory. The original structure of the wavelet network is obtained through a time-frequency analysis. Then the redundant nodes are eliminated in light of the dependency between the output of the network and nodes in the hidden layers to optimize the structure of the wavelet network. Simulation results show the proposed method is simple and effective.
  • Keywords
    neural nets; optimisation; rough set theory; time-frequency analysis; wavelet transforms; attribute dependency; redundant nodes; rough set theory; structure optimization; time-frequency analysis; wavelet frame; wavelet neural network; Automation; Intelligent control; Neural networks; Power engineering; Rough sets; Set theory; Time frequency analysis; Wavelet analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
  • Print_ISBN
    0-7803-7268-9
  • Type

    conf

  • DOI
    10.1109/WCICA.2002.1022193
  • Filename
    1022193