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
fDate :
9/1/2000 12:00:00 AM
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;
Journal_Title :
Automatic Control, IEEE Transactions on