• DocumentCode
    3450561
  • Title

    Modified BP neural network model is used for oddeven discrimination of integer number

  • Author

    Lian Tongli ; Xie Minxiang ; Xu Jiren ; Chen Ling ; Gao Huaihui

  • Author_Institution
    Dept. of Inf., Electron. Eng. Inst. of Hefei, Hefei, China
  • fYear
    2013
  • fDate
    7-9 Sept. 2013
  • Firstpage
    67
  • Lastpage
    70
  • Abstract
    This paper introduced the BP neural network model and the BP algorithm in detail, and points out the BP neural network exists the defects of local optimal tendency of local optimal, slow convergence speed etc. Through the introduction of modified BP algorithm, we can solve the problems existing in the traditional BP algorithm successfully, simulation results for odd-even discrimination of integer number based on MATLAB BP algorithm show that modified BP model compared with BP model, has faster training speed and high study accuracy. Modified BP neural network models is used in practice, as long as it is complementary with effective measures, and we can get satisfactory result completely.
  • Keywords
    backpropagation; convergence of numerical methods; learning (artificial intelligence); mathematics computing; optical neural nets; BP neural network model; MATLAB BP algorithm; convergence speed; integer number; local optimal tendency; odd-even discrimination; training speed; Algorithm design and analysis; Biological neural networks; Convergence; Mathematical model; Neurons; Training; BP neural network; modified BP algorithm; odd-even discrimination;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Optoelectronics and Microelectronics (ICOM), 2013 International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4799-1214-8
  • Type

    conf

  • DOI
    10.1109/ICoOM.2013.6626492
  • Filename
    6626492