Title :
Optimal stationary linear filtering for systems with Markov switching parameters
Author_Institution :
Dept. de Engenharia Eletronica, Sao Paulo Univ., Brazil
Abstract :
The stationary minimum mean square error estimator for discrete time linear systems with Markov switching parameters is considered for the case when the output sequence and mode of operation of the system are directly observable. It is shown that the solution of this problem is associated to a set of coupled algebraic Riccati-like equations. Conditions for the existence and uniqueness of a positive semi-definite solution are obtained via the convergence of a sequence of solutions of Lyapunov-like equations
Keywords :
Lyapunov methods; Markov processes; difference equations; discrete time systems; filtering and prediction theory; least squares approximations; linear systems; nonlinear differential equations; optimisation; Lyapunov-like equations; Markov switching parameters; coupled algebraic Riccati-like equations; discrete time linear systems; optimal stationary linear filtering; positive semi-definite solution; stationary minimum mean square error estimator; Hilbert space; Linear systems; Maximum likelihood detection; Mean square error methods; Nonlinear filters; Riccati equations; Stability;
Conference_Titel :
Decision and Control, 1993., Proceedings of the 32nd IEEE Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-1298-8
DOI :
10.1109/CDC.1993.325031
