• DocumentCode
    2578198
  • Title

    A recursive system identification method based on binary measurements

  • Author

    Jafari, Kian ; Juillard, Jerome ; Colinet, Eric

  • Author_Institution
    Dept. of Signal Process. & Electron. Syst., SUPELEC, Gif-sur-Yvette, France
  • fYear
    2010
  • fDate
    15-17 Dec. 2010
  • Firstpage
    1154
  • Lastpage
    1158
  • Abstract
    An online approach to parameter estimation problems based on binary observations is presented in this paper. This recursive identification method relies on a least-mean squares approach which makes it possible to estimate the coefficients of a finite-impulse response system knowing only the system input and the sign of the system output. The impulse response is identified up to a positive multiplicative constant. The role of the regulative coefficient is investigated thanks to simulated data. The proposed method is compared with another online approach: it is shown that the proposed method is competitive with the other one in terms of estimation quality and of calculation complexity.
  • Keywords
    FIR filters; least mean squares methods; recursive estimation; binary measurement; finite-impulse response system; least mean squares method; parameter estimation; recursive system identification method; Built-in self-test; Context; Convergence; Estimation; Least squares approximation; Noise; Parameter estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2010 49th IEEE Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4244-7745-6
  • Type

    conf

  • DOI
    10.1109/CDC.2010.5717798
  • Filename
    5717798