• DocumentCode
    2592423
  • Title

    Input Values Function for Improving Generalization Capability of BP Neural Network

  • Author

    He, Tongzhi ; Zheng, Shijue ; Zhang, Ping ; Zou, Ming

  • Author_Institution
    Dept. of Comput. Sci., Hua Zhong Normal Univ., Wuhan, China
  • fYear
    2010
  • fDate
    17-18 April 2010
  • Firstpage
    228
  • Lastpage
    231
  • Abstract
    As is known to all, Back propagation (BP) neural network has two important advantage and disadvantage: learning speed and generalization capability (GC). In this paper, we propose a new method by adding input values function (IVF) to improve the generalization of BP neural network. The result shows: GC in a certain extent has been improved throught this method. But if we want to do much more promoting in various fields, there are still a lot of things that we must to be studied.
  • Keywords
    backpropagation; neural nets; BP Neural Network; GC; back propagation; generalization capability improvement; input values function; Algorithm design and analysis; Computer science; Education; Feedforward systems; Helium; Multi-layer neural network; Neural networks; Neurons; System testing; Wearable computers; BP neural network; Generalization Capability; Input Values Function;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wearable Computing Systems (APWCS), 2010 Asia-Pacific Conference on
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-1-4244-6467-8
  • Electronic_ISBN
    978-1-4244-6468-5
  • Type

    conf

  • DOI
    10.1109/APWCS.2010.64
  • Filename
    5480505