• DocumentCode
    3787584
  • Title

    Nonparametric regression estimation by normalized radial basis function networks

  • Author

    A. Krzyzak;D. Schafer

  • Author_Institution
    Dept. of Comput. Sci. & Software Eng., Concordia Univ., Montreal, Que., Canada
  • Volume
    51
  • Issue
    3
  • fYear
    2005
  • Firstpage
    1003
  • Lastpage
    1010
  • Abstract
    This paper establishes weak and strong universal consistency of regression estimates based on normalized radial basis function networks when the network parameters are chosen by empirical risk minimization.
  • Keywords
    "Radial basis function networks","Kernel","Risk management","Multilayer perceptrons","Interpolation","Smoothing methods","Regression analysis","Eigenvalues and eigenfunctions","Neural networks"
  • Journal_Title
    IEEE Transactions on Information Theory
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2004.842632
  • Filename
    1397936
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3787584