• DocumentCode
    3645707
  • Title

    Prediction of chaos and bifurcation: an asymmetric basis function approach

  • Author

    H. Shibayama;T. Saito

  • Author_Institution
    EEE Dept., Hosei Univ., Tokyo, Japan
  • Volume
    4
  • fYear
    1997
  • Firstpage
    2251
  • Abstract
    This paper proposes an asymmetric basis function (ABF) network and considers its application for prediction of chaotic time series and bifurcation phenomena. Using chaotic time series from an autonomous circuit, we have performed numerical simulation for the prediction problems and have confirmed that the ABF network has much better performance than conventional RBF networks.
  • Keywords
    "Chaos","Bifurcation","Radial basis function networks","Sampling methods","Diodes","Switches","Gaussian processes","Circuits","Convergence","Equations"
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks,1997., International Conference on
  • Print_ISBN
    0-7803-4122-8
  • Type

    conf

  • DOI
    10.1109/ICNN.1997.614391
  • Filename
    614391