• DocumentCode
    3066783
  • Title

    The recursive linear identification method for ARMA model estimation

  • Author

    Liang, G. ; Wilkes, D.M.

  • Author_Institution
    Dept. of Electr. Eng., Vanderbilt Univ., Nashville, TN, USA
  • fYear
    1992
  • fDate
    12-15 Apr 1992
  • Firstpage
    677
  • Abstract
    A novel recursive method for estimating the parameters of autoregressive moving-average (ARMA) models is presented. The recursive linear identification method is basically developed from an offline linear identification technique due to J. Durbin (1960). An integral part of this approach requires the fitting of a large order autoregressive model to the data. The appropriate choice of the size of this model is also discussed. Simulation results are given to illustrate the performance of the proposed algorithm
  • Keywords
    identification; parameter estimation; recursive functions; spectral analysis; statistical analysis; ARMA model estimation; autoregressive moving-average; parameter estimation; recursive linear identification method; spectral analysis; Computational modeling; Parameter estimation; Polynomials; Random processes; Recursive estimation; White noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Southeastcon '92, Proceedings., IEEE
  • Conference_Location
    Birmingham, AL
  • Print_ISBN
    0-7803-0494-2
  • Type

    conf

  • DOI
    10.1109/SECON.1992.202282
  • Filename
    202282