• DocumentCode
    813646
  • Title

    Estimation of parameters in a partially whitened representation of a stochastic process

  • Author

    Kashyap, R.L.

  • Author_Institution
    Purdue University, Lafayette, IN, USA
  • Volume
    19
  • Issue
    1
  • fYear
    1974
  • fDate
    2/1/1974 12:00:00 AM
  • Firstpage
    13
  • Lastpage
    21
  • Abstract
    For a process which may not obey a stochastic linear difference equation (SDE) excited by white noise (i.e., ARMA equation), we will develop an SDE of prespecified order ( n,m ), excited by an "approximate white" noise. (The sense of approximation will be made precise in the text.) The corresponding representation is called the partially whitened representation (PWR) of order ( n,m ) for the process. A recursive method of parameter estimation is presented, and the accuracy of the estimates will be determined by analytical and simulation methods. The algorithm will asymptotically converge to the vector of coefficients of the ARMA ( n,m ) equation for the process, provided the process obeys such an equation. Otherwise, the algorithm will converge to the vector of coefficients of the PWR of order ( n,m ) for the process.
  • Keywords
    Autoregressive processes; Moving-average processes; Parameter estimation; Recursive estimation; Stochastic processes; Analytical models; Convergence; Difference equations; Filters; Parameter estimation; Recursive estimation; Stochastic processes; Stochastic resonance; White noise;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.1974.1100459
  • Filename
    1100459