• DocumentCode
    814491
  • Title

    Chaotifying linear Elman networks

  • Author

    Li, Xiang ; Chen, Guanrong ; Chen, Zengqiang ; Yuan, Zhuzhi

  • Author_Institution
    Dept. of Autom., Nankai Univ., Tianjin, China
  • Volume
    13
  • Issue
    5
  • fYear
    2002
  • fDate
    9/1/2002 12:00:00 AM
  • Firstpage
    1193
  • Lastpage
    1199
  • Abstract
    A linear model of recurrent neural networks, called the Elman networks, is combined with the simple nonlinear modulo (mod) operation on its linear activated function so as to generate chaos purposely. Conditions on the weight matrix are obtained, under which the generated chaos satisfies the mathematical definition of chaos in the sense of T.Y. Li and J.A. Yorke (1975). Some simple and representative weight matrices are constructed for designing such Elman networks that can generate Li-Yorke chaos. Several numerical simulations are shown to verify and visualize the design.
  • Keywords
    chaos; matrix algebra; recurrent neural nets; Li-Yorke chaos; chaos; chaotification; linear Elman networks; linear activated function; linear model; mathematical definition; recurrent neural networks; simple nonlinear modulo operation; weight matrices; weight matrix; Automation; Biological neural networks; Chaos; Humans; Neurofeedback; Neurons; Numerical simulation; Recurrent neural networks; State feedback; Visualization;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/TNN.2002.1031950
  • Filename
    1031950