• DocumentCode
    571567
  • Title

    Improved Wavelet Networks Algorithm Research and its Application

  • Author

    Jin-tian, Yin ; Jie, Tang ; Li, Liu

  • Author_Institution
    Dept. of Electr. Eng., Hunan Univ. of Shaoyang, Shaoyang, China
  • Volume
    1
  • fYear
    2012
  • fDate
    26-27 Aug. 2012
  • Firstpage
    17
  • Lastpage
    20
  • Abstract
    The conventional learning algorithm based on BP method may converge to a local minimum, slowly converging speed and is shock before and after the Convergence point. A algorithm based on BP and PID techniques for wavelet network learning was proposed. And PIDBP algorithm can significantly reduce the probability of the emergence of local minimum after adding momentum term, At the same time introduction of the inertia term, Can be in the larger learning parameters to speed up the convergence and divergence and to reduce the possibility of oscillation, And avoid conventional BP algorithm in the convergence region Insensitivity to accelerate the convergence.
  • Keywords
    backpropagation; convergence; learning (artificial intelligence); wavelet transforms; BP method; PID techniques; convergence region insensitivity; divergence; improved wavelet networks algorithm research; inertia term; learning algorithm; local minimum; momentum term; Convergence; Equations; Heuristic algorithms; Neural networks; Signal processing algorithms; Training; Wavelet transforms; BP algorithm; Inertia term; Momentum term; PIDBP algorithm; Wavelet Networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2012 4th International Conference on
  • Conference_Location
    Nanchang, Jiangxi
  • Print_ISBN
    978-1-4673-1902-7
  • Type

    conf

  • DOI
    10.1109/IHMSC.2012.10
  • Filename
    6305614