• DocumentCode
    1684893
  • Title

    On-line identification of nonlinear systems using adaptive matching pursuit

  • Author

    Shmilovici, Armin ; Maimon, Oded

  • Author_Institution
    Dept. of Manuf. Eng., Boston Univ., MA, USA
  • fYear
    1996
  • Firstpage
    499
  • Lastpage
    502
  • Abstract
    A reduced complexity algorithm, which is an adaptive version of the matching pursuit algorithm, is proposed for the identification of nonlinear systems. The algorithm is demonstrated on various nonlinear systems presented in the literature. The results are favorable compared to other nonlinear identification methods (e.g neural nets). It is demonstrated that the algorithm could be used for the design of adaptive controllers
  • Keywords
    adaptive control; adaptive filters; adaptive signal processing; computational complexity; identification; nonlinear control systems; adaptive controllers; adaptive matching pursuit; matching pursuit algorithm; nonlinear systems; on-line identification; reduced complexity algorithm; Adaptive control; Adaptive filters; Adaptive systems; Dictionaries; Matching pursuit algorithms; Neural networks; Nonlinear systems; Programmable control; Pursuit algorithms; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Electronics Engineers in Israel, 1996., Nineteenth Convention of
  • Conference_Location
    Jerusalem
  • Print_ISBN
    0-7803-3330-6
  • Type

    conf

  • DOI
    10.1109/EEIS.1996.567025
  • Filename
    567025