• DocumentCode
    437048
  • Title

    Nonlinear systems using two-layer DBF neural networks and application for model identification structure

  • Author

    Wen-Ming, Cao ; Lu Fei ; Hao, Feng ; Shuojue, Wang

  • Author_Institution
    Inst. of Intell. Coll. of Inf. Eng., Zhejiang Univ. of Technol., Hangzhou, China
  • Volume
    1
  • fYear
    2004
  • fDate
    Aug. 31 2004-Sept. 4 2004
  • Firstpage
    583
  • Abstract
    Nonlinear system identification using direction basis function neural networks is presented. The state estimation error is proven to converge to zero asymptotically. Parameters of the identifier converge to the ideal parameters provided that persistency of excitation condition is fulfilled. The multiple model identification structure is analyzed.
  • Keywords
    feedforward neural nets; neural nets; nonlinear systems; state estimation; direction basis function neural network; model identification structure; nonlinear system; state estimation error; two-layer DBF neural network; Convergence; Educational institutions; Electrostatic precipitators; Estimation error; Filtering; Hardware; Multi-layer neural network; Neural networks; Neurons; Nonlinear systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-8406-7
  • Type

    conf

  • DOI
    10.1109/ICOSP.2004.1452729
  • Filename
    1452729
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=437048