• DocumentCode
    894757
  • Title

    A QR-type algorithm for fitting the delta AR model to autocorrelation windowed data

  • Author

    Zarowski, Christopher J.

  • Author_Institution
    Dept. of Electr. Eng., Queen´´s Univ., Kingston, Ont., Canada
  • Volume
    41
  • Issue
    4
  • fYear
    1993
  • fDate
    4/1/1993 12:00:00 AM
  • Firstpage
    1728
  • Lastpage
    1730
  • Abstract
    A QR algorithm is developed to fit the delta autoregressive (DAR) model of Vijayan et al. (see IEEE Trans. Automat. Cont. vol.36, p.314, 1991) to autocorrelation windowed sampled data. To obtain the DAR model parameters, one must solve a linear system in the matrix called Qn. Unfortunately, there is presently no way to obtain good estimates of Qn. The proposed QR-type algorithm overcomes this problem by computing the DAR model parameters without the need for estimating Qn directly. The QR algorithm proposed is a simple modification of the classical QR algorithm for the conventional AR model due to C.P. Rialan and L.L. Scharf (1986)
  • Keywords
    correlation theory; matrix algebra; signal processing; QR algorithm; autocorrelation windowed data; delta AR model; linear system; matrix; model parameters; sampled data; Autocorrelation; Filtering; Kalman filters; Linear systems; Riccati equations; Sampling methods; Signal processing algorithms; State feedback;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.212757
  • Filename
    212757