• DocumentCode
    2437810
  • Title

    Fractal neural networks for short term memory

  • Author

    Li, X. ; Wong, W.S.

  • Author_Institution
    Dept. of Inf. Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong
  • Volume
    4
  • fYear
    1994
  • fDate
    27 Jun-2 Jul 1994
  • Firstpage
    2454
  • Abstract
    Synaptic connection matrix encodes limited information. It is well known that neural network memory with storage prescriptions based on Hebb´s rule will collapse as more patterns are stored. By requiring that old patterns be automatically forgotten and the memory recall only the most recently ones, a new short-term neural network memory based on Y. Baram´s fractal neural network is obtained. Comparison is drawn with Morris and Wong´s method and the experimental results are shown to be rather satisfactory and encouraging
  • Keywords
    content-addressable storage; error statistics; fractals; learning (artificial intelligence); neural nets; error probability; fractal neural networks; learning algorithm; short term memory; synaptic matrix; Application software; Associative memory; Biological system modeling; Computer network reliability; Fractals; Neural networks; Neurofeedback; Neurons; Pattern analysis; Terminology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-1901-X
  • Type

    conf

  • DOI
    10.1109/ICNN.1994.374605
  • Filename
    374605