• DocumentCode
    1402123
  • Title

    Gradient of the log-likelihood ratio for infinite dimensional stochastic systems

  • Author

    Leland, Robert P.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Alabama Univ., Tuscaloosa, AL, USA
  • Volume
    45
  • Issue
    9
  • fYear
    2000
  • fDate
    9/1/2000 12:00:00 AM
  • Firstpage
    1770
  • Lastpage
    1774
  • Abstract
    Using a covariance operator approach, we derive an expression for the log-likelihood ratio gradient for system parameter estimation for continuous-time infinite-dimensional stochastic systems. The gradient formula includes the smoother estimates and derivatives of system operators, with no derivatives of estimates or covariance operators. The unbounded operators typically found in partial differential equations limit how much the gradient formula can be simplified. A random heat equation is considered
  • Keywords
    continuous time systems; distributed parameter systems; maximum likelihood estimation; partial differential equations; stochastic systems; covariance operator approach; infinite dimensional stochastic systems; log-likelihood ratio; random heat equation; unbounded operators; Automatic control; Control systems; Feedback; Maximum likelihood estimation; Nonlinear control systems; Predictive control; Predictive models; Robust control; Stability; Stochastic systems;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/9.880646
  • Filename
    880646