• DocumentCode
    397834
  • Title

    Multiwavelet neural network: a novel model

  • Author

    Li, Xiaolan ; Gao, Xieping

  • Author_Institution
    Nat. Lab. on Machine Perception, Peking Univ., Beijing, China
  • Volume
    3
  • fYear
    2003
  • fDate
    5-8 Oct. 2003
  • Firstpage
    2629
  • Abstract
    A neural network is an efficient tool to solve nonlinear problem, but it is hard to determine its structure and it often settles in a local minimum. After combining the wavelet with it, the two key problems are solved. However, a new problem, so called "dimension disaster", appears, and solving it within the framework of a wavelet neural network (WNN) is not easy. We introduce a new neural network named multiwavelet neural network (MWNN), which not only preserves all the advantages of WNN, but also avoids the "dimension disaster". Several theorems are given and the experimental results validate the correctness of our theory.
  • Keywords
    feedforward neural nets; wavelet transforms; dimension disaster; local minimum; multiwavelet neural network; nonlinear problem; Educational institutions; Feedforward neural networks; Frequency; Multi-layer neural network; Multiresolution analysis; Neural networks; Numerical analysis; Signal processing; Signal processing algorithms; Wavelet analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2003. IEEE International Conference on
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-7952-7
  • Type

    conf

  • DOI
    10.1109/ICSMC.2003.1244280
  • Filename
    1244280