• DocumentCode
    518696
  • Title

    A fast OBS pruning algorithm based on pseudo-entropy of weights

  • Author

    Zhao, Shouling ; Liu, Quan ; Zhang, Binbin

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Soochow Univ., Suzhou, China
  • Volume
    3
  • fYear
    2010
  • fDate
    27-29 March 2010
  • Firstpage
    451
  • Lastpage
    455
  • Abstract
    A fast OBS pruning algorithm based on pseudo-entropy of weights is proposed to resolve the problems of the number of hidden neurons is difficult to be determined in neural networks and low pruning speed in conventional OBS (Optimal Brain Surgeon) pruning algorithm. The algorithm makes the network constrain the distribution of weight automatically during the training process, obtain a simpler structure of network, and improve the speed of pruning. The result of experimental shows that the structure of network has been simplified; the generalization capability of network and the speed of pruning have been improved greatly by using the algorithm mentioned above.
  • Keywords
    backpropagation; entropy; generalisation (artificial intelligence); neural nets; OBS pruning algorithm; generalization capability; neural networks; optimal brain surgeon pruning algorithm; weight pseudoentropy; Biological neural networks; Computer networks; Computer science; Entropy; Feeds; Information theory; Network topology; Neurons; Optimization methods; Surges; BP neural network; OBS pruning algorithm; generalization capability; pseudo-entropy of weights;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computer Control (ICACC), 2010 2nd International Conference on
  • Conference_Location
    Shenyang
  • Print_ISBN
    978-1-4244-5845-5
  • Type

    conf

  • DOI
    10.1109/ICACC.2010.5486816
  • Filename
    5486816