• DocumentCode
    2830648
  • Title

    Pattern dynamics of chaotic neural networks with nearest-neighbor couplings

  • Author

    Adachi, M. ; Aihara, K. ; Kotani, M.

  • Author_Institution
    Dept. of Electron. Eng., Tokyo Denki Univ., Japan
  • fYear
    1991
  • fDate
    11-14 Jun 1991
  • Firstpage
    1180
  • Abstract
    The authors introduce chaos into simple mathematical neuron models which are deterministic rather than probabilistic. The authors apply chaotic dynamics to artificial neural networks, using a chaotic neuron model based on electrophysiological experiments with squid giant axons and on numerical experiments with the Hodgkin-Huxley equations. First, the authors explain the chaotic neuron model and its dynamics. The authors also demonstrate spatio-temporal pattern dynamics of chaotic neural networks with nearest-neighbor couplings. It is shown that the chaotic neural networks with nearest-neighbor couplings have abundant spatio-temporal dynamics with a possible applicability to dynamical spatio-temporal memory
  • Keywords
    brain models; chaos; neural nets; pattern recognition; Hodgkin-Huxley equations; artificial neural networks; chaotic dynamics; chaotic neural networks; chaotic neuron model; dynamical spatio-temporal memory; electrophysiological experiments; mathematical neuron models; nearest-neighbor couplings; spatio-temporal pattern dynamics; squid giant axons; Artificial neural networks; Bifurcation; Biological neural networks; Chaos; Equations; Integrated circuit modeling; Multi-layer neural network; Neural networks; Neurofeedback; Neurons;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1991., IEEE International Sympoisum on
  • Print_ISBN
    0-7803-0050-5
  • Type

    conf

  • DOI
    10.1109/ISCAS.1991.176578
  • Filename
    176578