• DocumentCode
    277908
  • Title

    The feasibility of using MLP neural networks for system identification

  • Author

    Chen, J.R. ; Mars, P.

  • Author_Institution
    Sch. of Eng. & Appl. Sci., Durham Univ., UK
  • fYear
    1991
  • fDate
    33263
  • Firstpage
    42430
  • Lastpage
    42432
  • Abstract
    Recently, there has been considerable interest in the use of artificial neural networks for system identification and control. In this paper the authors discuss some constraints faced by using the Model-I and Model-II neural network systems introduced in work by K.S. Narendra and K. Parthasarathy (see IEEE Tranc. on Neural Networks, vol.1, no.1, p.4-27 (1990)) for nonlinear system identification
  • Keywords
    identification; neural nets; nonlinear systems; MLP; multilayer perceptron; neural networks; nonlinear system; system identification;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Neural Networks for Systems: Principles and Applications, IEE Colloquium on
  • Conference_Location
    London
  • Type

    conf

  • Filename
    180906