• DocumentCode
    1738148
  • Title

    Search time of cyclic patterns in chaotic neural network

  • Author

    Deguchi, T. ; Ishii, N.

  • Author_Institution
    Gifu Nat. Coll. of Technol., Japan
  • Volume
    1
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    401
  • Abstract
    The chaotic neural networks that learn patterns by associative memory can recall aperiodic pattern sequences including the learned ones. We report that applying presynaptic inhibition to a chaotic neural network to control the chaotic behavior realized the search of cyclic associative memory by matching features with chaos. Nara et al. (1992) reported the search of cyclic associative memory by changing the connection number of neurons. Using the patterns the same as Nara´s report, the same searches ware carried out in chaotic neural networks. The results shows that search by the chaotic neural network can attain a better success rate, but the speed is lower. To improve the time for search the presynaptic inhibition function is reformed
  • Keywords
    chaos; content-addressable storage; learning (artificial intelligence); neural nets; search problems; aperiodic pattern sequences; chaos; chaotic neural network; cyclic associative memory; cyclic pattern search time; pattern learning; presynaptic inhibition; Associative memory; Biological system modeling; Chaos; Computer science; Educational institutions; Information processing; Intelligent networks; Neural networks; Neurons; State-space methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge-Based Intelligent Engineering Systems and Allied Technologies, 2000. Proceedings. Fourth International Conference on
  • Conference_Location
    Brighton
  • Print_ISBN
    0-7803-6400-7
  • Type

    conf

  • DOI
    10.1109/KES.2000.885841
  • Filename
    885841