• DocumentCode
    2565733
  • Title

    The robustness of combination of sigmoid function wavelet neural network

  • Author

    Xia, Hou ; Shousong, Hu ; Liu Guo Hai

  • Author_Institution
    Sch. of Electr. & Inf. Eng., Jiangsu Univ., Zhenjiang
  • fYear
    2008
  • fDate
    2-4 July 2008
  • Firstpage
    3494
  • Lastpage
    3499
  • Abstract
    The disturbing sensitivity and robustness of combination of sigmoid function wavelet neural network are discussed by making use of probability statistics and symbolic logic. If the faint perturbation appears, the robust invariability condition of wavelet neural network is obtained, and if the sensitive disturbance appears, the sensitivity formula and robustness formula are given. It is proved theoretically that to a certain extent, the more hidden wavelet nerve cells, the less robustness of wavelet neural network. Consequently, it validates analytically the intuitionistic hypothesis of the relationship between hidden layer wavelet nerve cells number and the robustness of wavelet neural network.
  • Keywords
    neural nets; statistical analysis; wavelet transforms; Sigmoid function wavelet neural network; disturbing sensitivity; hidden layer wavelet nerve cells; intuitionistic hypothesis; probability statistics; symbolic logic; Automation; Educational institutions; Electronic mail; Logic; Neural networks; Probability; Robustness; Statistics; Wavelet analysis; Zinc; Faint Perturbation; Robustness; Sensitive Disturbance; Sensitivity; Wavelet Neural Network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2008. CCDC 2008. Chinese
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-1733-9
  • Electronic_ISBN
    978-1-4244-1734-6
  • Type

    conf

  • DOI
    10.1109/CCDC.2008.4597979
  • Filename
    4597979