• DocumentCode
    3250415
  • Title

    Self-generating neural networks

  • Author

    Wen, Wilson X. ; Liu, Huan ; Jennings, Andrew

  • Author_Institution
    Telecom Res. Lab., Clayton, Vic., Australia
  • Volume
    4
  • fYear
    1992
  • fDate
    7-11 Jun 1992
  • Firstpage
    850
  • Abstract
    A method for generating neural networks automatically is proposed. Not only the weights of the connections but also the structure of the network including the number of neurons, the number of layers, and the interconnections among the neurons are all learned from the training examples. Issues of optimization and pruning of the generated networks are investigated. An experimental system has been implemented based on the proposed method and some experimental results and comparisons between this method and other methods are also given
  • Keywords
    learning by example; optimisation; self-organising feature maps; layers; learning by examples; neurons; optimization; pruning; self-generating neural networks; Artificial intelligence; Feedforward neural networks; Humans; Multi-layer neural network; Neural networks; Neurons; Resonance; Self-organizing networks; Tree data structures; Tree graphs;
  • 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.1992.227211
  • Filename
    227211