• DocumentCode
    1816483
  • Title

    An error correcting algorithm for Hopfield network

  • Author

    Hui, Chi-Chung ; Chan, Lai-Wan

  • Author_Institution
    Dept. of Comput Sci., Chinese Univ. of Hong Kong, Shatin, Hong Kong
  • Volume
    1
  • fYear
    1992
  • fDate
    7-11 Jun 1992
  • Firstpage
    920
  • Abstract
    The principle and the weakness of the Hopfield network are discussed. It is found that the assumption that the Hopfield network made on the noise effect of input patterns is inappropriate and an adaptive training algorithm that minimizes the noise effect of the input patterns is presented. This algorithm alters the connection weights of the network. It is shown that the storage capacity of the resultant model increases from 0.16n to greater than 1.14n, where n is the number of neurons in the network. Moreover, the model has a higher error tolerance level than the original model
  • Keywords
    Hopfield neural nets; error correction; learning (artificial intelligence); Hopfield network; adaptive training algorithm; connection weights; error correcting algorithm; error tolerance level; input patterns; neurons; noise effect; storage capacity; Adaptive algorithm; Computer errors; Computer science; Equations; Error correction; Neurons; Random number generation; Test pattern generators; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1992. IJCNN., International Joint Conference on
  • Conference_Location
    Baltimore, MD
  • Print_ISBN
    0-7803-0559-0
  • Type

    conf

  • DOI
    10.1109/IJCNN.1992.287069
  • Filename
    287069
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1816483