• DocumentCode
    1622523
  • Title

    Identification of nonlinear systems with a dynamic recurrent neural network

  • Author

    Delgado, A. ; Kambhampati, C. ; Warwick, K.

  • Author_Institution
    Reading Univ., UK
  • fYear
    1995
  • Firstpage
    318
  • Lastpage
    322
  • Abstract
    Two approaches are presented to calculate the weights for a Dynamic Recurrent Neural Network (DRNN) in order to identify the input-output dynamics of a class of nonlinear systems. The number of states of the identified network is constrained to be the same as the number of states of the plant
  • Keywords
    identification; nonlinear systems; recurrent neural nets; dynamic recurrent neural network; identification; identified network; nonlinear systems; states;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Artificial Neural Networks, 1995., Fourth International Conference on
  • Conference_Location
    Cambridge
  • Print_ISBN
    0-85296-641-5
  • Type

    conf

  • DOI
    10.1049/cp:19950575
  • Filename
    497838
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1622523