• DocumentCode
    176981
  • Title

    Asymptotical behavior of parameter estimation in prediction error framework

  • Author

    Caiyun Chen ; Zhibin Yan

  • Author_Institution
    Natural Sci. Res. Center, Harbin Inst. of Technol., Harbin, China
  • fYear
    2014
  • fDate
    May 31 2014-June 2 2014
  • Firstpage
    4496
  • Lastpage
    4500
  • Abstract
    In prediction error method, it is known that the sequence of the criterion function converges uniformly in the parameter with probability one as the length of the input-output data tends to infinity. When the minimizing points of the limiting function criterion are not unique, the convergence of parameter estimation is not guaranteed in general. Two cases are distinguished. The case one is that the set of the minimizing points of the limiting function criterion is a continuum, and the case two is that the points of that set are isolated. Some interesting phenomena relating to the different cases are shown about the asymptotical behavior of parameter estimation through examples and theoretical analysis.
  • Keywords
    convergence; parameter estimation; probability; asymptotical behavior; convergence; criterion function; input-output data; limiting function criterion; parameter estimation; prediction error framework; prediction error method; probability; Convergence; Estimation; Limiting; Measurement; Parameter estimation; Vectors; White noise; Hausdorff metric; parameter estimation; prediction error method; system identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (2014 CCDC), The 26th Chinese
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4799-3707-3
  • Type

    conf

  • DOI
    10.1109/CCDC.2014.6852974
  • Filename
    6852974