• DocumentCode
    1403539
  • Title

    Comments on "Approximation capability in C(R/sup n/) by multilayer feedforward networks and related problems"

  • Author

    Guang-Bin Huang ; Babri, H.A.

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
  • Volume
    9
  • Issue
    4
  • fYear
    1998
  • fDate
    7/1/1998 12:00:00 AM
  • Firstpage
    714
  • Lastpage
    715
  • Abstract
    In the above paper Chen et al. (ibid., vol.6 (1995)) investigated the capability of uniformly approximating functions in C(R/sup n/) by standard feedforward neural networks. They found that the boundedness condition on the sigmoidal function plays an essential role in the approximation, and conjectured that the boundedness of the sigmoidal function is a necessary and sufficient condition for the validity of the approximation theorem. However, we find that the conjecture is not correct, that is, the boundedness condition is not sufficient or necessary in C(R/sup n/). Instead, boundedness and unequal limits at infinities conditions on the activation functions are sufficient, but not necessary in C(R/sup n/).
  • Keywords
    feedforward neural nets; function approximation; transfer functions; activation functions; boundedness condition; feedforward neural networks; function approximation; multilayer neural networks; necessary condition; sigmoidal function; sufficient condition; Feedforward neural networks; H infinity control; Intelligent networks; Multi-layer neural network; Neural networks; Nonhomogeneous media; Sufficient conditions;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/72.701184
  • Filename
    701184