• DocumentCode
    2109723
  • Title

    The best approximation properties and error bounds of Gaussian networks

  • Author

    Liu, Binfan ; Si, Jennie

  • Author_Institution
    Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ, USA
  • fYear
    1993
  • fDate
    15-17 Dec 1993
  • Firstpage
    2798
  • Abstract
    The best approximation of any C2 function with support on the unit hypercube Im in Rm is considered in the present paper. We prove that a Gaussian radial basis network with centers defined on a regular mesh in Rm has the best approximation property. Moreover, an upper bound (O(N-2)) of the approximation is obtained for a network having Nm units
  • Keywords
    computational complexity; error analysis; feedforward neural nets; function approximation; Gaussian radial basis network; best approximation; error bounds; unit hypercube; upper bound; Feedforward neural networks; Gaussian approximation; Green´s function methods; Hypercubes; Integral equations; Measurement standards; Neural networks; Nonhomogeneous media; Radial basis function networks; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1993., Proceedings of the 32nd IEEE Conference on
  • Conference_Location
    San Antonio, TX
  • Print_ISBN
    0-7803-1298-8
  • Type

    conf

  • DOI
    10.1109/CDC.1993.325705
  • Filename
    325705
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2109723