• DocumentCode
    700730
  • Title

    L2 approximation properties of recurrent neural networks

  • Author

    Ruiz, A. ; Owens, D.H. ; Townley, S.

  • Author_Institution
    Centre for Syst. & Control Eng., Univ. of Exeter, Exeter, UK
  • fYear
    1997
  • fDate
    1-7 July 1997
  • Firstpage
    1773
  • Lastpage
    1778
  • Abstract
    We introduce a class of recurrent neural network that learn and replicates a periodic L2 function. A gradient type algorithm is used to modify the parameters of the network so that it learns and replicates autonomously a periodic signal. An example illustrates the results.
  • Keywords
    approximation theory; learning (artificial intelligence); recurrent neural nets; L2 approximation properties; autonomous periodic signal learning; autonomous periodic signal replication; gradient type algorithm; network parameters; periodic L2 function; recurrent neural networks; Approximation methods; Biological neural networks; Heuristic algorithms; Limit-cycles; Minimization; Recurrent neural networks; Roads; Intelligent Control; Neural Networks; Nonlinear Dynamics; Periodic Systems; Recurrent Neural Networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (ECC), 1997 European
  • Conference_Location
    Brussels
  • Print_ISBN
    978-3-9524269-0-6
  • Type

    conf

  • Filename
    7082360
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=700730