• DocumentCode
    684758
  • Title

    Monotonicity of asynchronous gradient method for RPNN

  • Author

    Xin Yu ; Lixia Tang ; Yan Yu

  • Author_Institution
    Sch. of Comput., Electron. & Inf., Guangxi Univ., Nanning, China
  • fYear
    2012
  • fDate
    7-9 Dec. 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The Ridge Polynomial neural network is one of the most popular higher-order neural networks, which has the powerful capability of approximating reasonable functions. In order to select appropriate learning parameters to perform an efficient training, the monotonicity of asynchronous gradient method is proved for training Ridge Polynomial neural networks.
  • Keywords
    function approximation; gradient methods; learning (artificial intelligence); neural nets; RPNN; asynchronous gradient method monotonicity; higher-order neural networks; learning parameters; reasonable function approximation; ridge polynomial neural network training; Ridge Polynomial neural network; asynchronous gradient algorithm; monotonicity;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Information Science and Control Engineering 2012 (ICISCE 2012), IET International Conference on
  • Conference_Location
    Shenzhen
  • Electronic_ISBN
    978-1-84919-641-3
  • Type

    conf

  • DOI
    10.1049/cp.2012.2344
  • Filename
    6755723
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=684758