• DocumentCode
    2347556
  • Title

    On Chaos Character of Dynamic Fuzzy Neural Network

  • Author

    Tang, Mo ; Wang, Kejun ; Bi, Xiaojun

  • Author_Institution
    Dept. of Autom., Harbin Eng. Univ., Harbin, China
  • fYear
    2011
  • fDate
    15-19 April 2011
  • Firstpage
    1011
  • Lastpage
    1015
  • Abstract
    The chaos character of dynamic fuzzy neural network is further explored and analyzed in this paper applying the traditional Lyapunov exponent method. Firstly, the working principle of dynamic fuzzy neural network is introduced, and then the discretization network model is given by Euler method. The dissipation and chaos traits of single dynamic fuzzy neuron and dynamic fuzzy neural networks are proved separately. According to Lyapunov exponent discriminance criterion, four conditions are deduced, which the parameters should satisfy to prove the existence of chaos in single dynamic neuron and dynamic fuzzy neural network.
  • Keywords
    Lyapunov methods; fuzzy neural nets; Euler method; Lyapunov exponent discriminance criterion; chaos character; discretization network model; dynamic fuzzy neural network; single dynamic fuzzy neuron; Artificial neural networks; Chaos; Fuzzy control; Fuzzy neural networks; Neurons; Nonlinear dynamical systems; Power system dynamics; Lyapunov exponent; chaos; dynamic fuzzy neruon; dynamic fuzzy neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference on
  • Conference_Location
    Yunnan
  • Print_ISBN
    978-1-4244-9712-6
  • Electronic_ISBN
    978-0-7695-4335-2
  • Type

    conf

  • DOI
    10.1109/CSO.2011.183
  • Filename
    5957828