• DocumentCode
    3493497
  • Title

    Dynamics of fractional-order neural networks

  • Author

    Kaslik, Eva ; Sivasundaram, Seenith

  • Author_Institution
    Inst. e-Austria, Timisoara, Romania
  • fYear
    2011
  • fDate
    July 31 2011-Aug. 5 2011
  • Firstpage
    611
  • Lastpage
    618
  • Abstract
    In this paper we discuss the stability analysis for fractional-order neural networks of Hopfield type. The stability domain of a steady state is completely characterized with respect to some characteristic parameters of the system, in the case of a two-dimensional network and of a network of n ≥ 3 neurons with ring structure. The values of the characteristic parameters for which Hopf bifurcations occur are identified. Numerical simulations are given which substantiate the theoretical findings and suggest possible routes towards chaos when the fractional order of the system increases.
  • Keywords
    Hopfield neural nets; bifurcation; numerical analysis; stability; Hopf bifurcations; Hopfleld type; fractional-order neural networks; numerical simulations; ring structure; stability analysis; two-dimensional network; Asymptotic stability; Bifurcation; Biological neural networks; Eigenvalues and eigenfunctions; Neurons; Stability analysis; Steady-state;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2011 International Joint Conference on
  • Conference_Location
    San Jose, CA
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4244-9635-8
  • Type

    conf

  • DOI
    10.1109/IJCNN.2011.6033277
  • Filename
    6033277