• DocumentCode
    328247
  • Title

    Removal of hidden units and weights for back propagation networks

  • Author

    Hagiwara, Masafumi

  • Author_Institution
    Fac. of Sci. & Technol., Keio Univ., Yokohama, Japan
  • Volume
    1
  • fYear
    1993
  • fDate
    25-29 Oct. 1993
  • Firstpage
    351
  • Abstract
    The objective of this paper is to present a simple and effective method for removal of both hidden units and weights. In this paper, we propose two methods, "consuming energy" method and "weights power" method, and compare them with the conventional method. According to our computer simulations using the mirror symmetry problem, the weights power method has shown the best performance in respect of size reduction (removal of units and weights), generalization performance, and the amount of computation required. For example, the number of hidden units reduced to about 40% of the initial state, and the number of weights reduced to less than a fourth of the initial state. In addition, generalization performance was improved more than 10%.
  • Keywords
    backpropagation; neural nets; back propagation neural networks; consuming energy method; hidden units removal; mirror symmetry problem; size reduction; weights power method; weights removal; Artificial neural networks; Computational efficiency; Computer simulation; Mirrors; Sonar; Speech recognition; Target recognition;
  • 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.1993.713929
  • Filename
    713929