• DocumentCode
    2971468
  • Title

    An extended BAM neural network model

  • Author

    Zhenjiang, Miao ; Baozong, Yuan

  • Author_Institution
    Inst. of Inf. Sci., Northern Jiaotong Univ., Beijing, China
  • Volume
    3
  • fYear
    1993
  • fDate
    25-29 Oct. 1993
  • Firstpage
    2682
  • Abstract
    Proposes an extended bidirectional associative memory (BAM) neural network model which can do auto- and hetero-associative memory. The theoretical proof for this neural network model´s stability is given. Experiments show that this neural network model is much more powerful than the M-P model, discrete Hopfield neural network, continuous Hopfield neural network, discrete bidirectional associative memory neural network, continuous and adaptive bidirectional associative memory neural network, backpropagation neural network and optimal designed nonlinear continuous neural network. Experimental results also show that, when it does auto-associative memory, the power of this model is the same as the loop neural network model which can only do auto-associative memory.
  • Keywords
    content-addressable storage; neural nets; M-P model; auto-associative memory; backpropagation neural network; continuous Hopfield neural network; discrete Hopfield neural network; discrete bidirectional associative memory neural network; extended BAM neural network model; extended bidirectional associative memory neural network; hetero-associative memory; model stability; optimal designed nonlinear continuous neural network; Adaptive systems; Artificial neural networks; Associative memory; Hopfield neural networks; Information science; Intelligent control; Magnesium compounds; Neural networks; Neurofeedback; Stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
  • Print_ISBN
    0-7803-1421-2
  • Type

    conf

  • DOI
    10.1109/IJCNN.1993.714276
  • Filename
    714276