• DocumentCode
    2674863
  • Title

    Maximum Likelihood, Weighted Kalman And Subspace Linear Prediction Algorithms For System Identification

  • Author

    Rua, Y. ; Sarkar, T.K.

  • Author_Institution
    Syracuse University
  • Volume
    2
  • fYear
    1988
  • fDate
    Oct. 31 1988-Nov. 2 1988
  • Firstpage
    715
  • Lastpage
    719
  • Abstract
    For the problem of estimating parameters of a linear system from its input and output sequences, we present iterative quadratic maximum likelihood (IQML), iterative quadratic weighted Kalman (IQWK), and noniterative subspace linear prediction (SLP) algorithms. The SLP algorithms are based on a novel subspace deconvolution of the output. In particular, a double total-least-squares (D-TLS) SLP algorithm is provided.
  • Keywords
    Contracts; Covariance matrix; Deconvolution; Iterative algorithms; Iterative methods; Kalman filters; Least squares approximation; Maximum likelihood estimation; Parameter estimation; Prediction algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers, 1988. Twenty-Second Asilomar Conference on
  • Conference_Location
    Pacific Grove, CA, USA
  • ISSN
    1058-6393
  • Type

    conf

  • DOI
    10.1109/ACSSC.1988.754643
  • Filename
    754643
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2674863