• DocumentCode
    1624859
  • Title

    Adaptive IIR system identification with fixed pole location via balanced model truncation

  • Author

    Pasquato, L. ; Kale, I. ; Cain, G.D.

  • Author_Institution
    Div. of Electron. Syst., Westminster Univ., London, UK
  • Volume
    1
  • fYear
    1997
  • Firstpage
    166
  • Abstract
    Adaptive filtering theory reveals obstacles concerning convergence and stability in the IIR situation. Here we show how to completely avoid the stability problem while also reducing convergence difficulties-all by the application of the Balanced Model Truncation (BMT) algorithm. The specific case of system identification is investigated
  • Keywords
    IIR filters; adaptive filters; circuit analysis computing; circuit stability; identification; adaptive IIR system identification; balanced model truncation; balanced model truncation algorithm; convergence; fixed pole location; obstacles; stability; system identification; Adaptive filters; Adaptive systems; Convergence; Finite impulse response filter; IIR filters; Least squares approximation; Robustness; Stability; System identification; Working environment noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation and Measurement Technology Conference, 1997. IMTC/97. Proceedings. Sensing, Processing, Networking., IEEE
  • Conference_Location
    Ottawa, Ont.
  • ISSN
    1091-5281
  • Print_ISBN
    0-7803-3747-6
  • Type

    conf

  • DOI
    10.1109/IMTC.1997.603936
  • Filename
    603936
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1624859