Title :
Optimal linear filtering for discrete-time Markovian jump linear systems
Author_Institution :
Dept. de Engenharia Eletronica, Sao Paulo, Brazil
Abstract :
Optimal linear state estimation for discrete-time linear systems subject to Markovian abrupt changes in the parameters is considered. It is not assumed that random sequences are Gaussian. The filter equations are derived in a recursive form, resulting in an online algorithm suitable for computer implementation
Keywords :
Markov processes; discrete time systems; filtering and prediction theory; linear systems; state estimation; discrete-time Markovian jump linear systems; optimal linear filtering; random sequences; state estimation; Equations; Gaussian distribution; Gaussian noise; Linear systems; Maximum likelihood detection; Nonlinear filters; Random sequences; Random variables; State estimation; State-space methods;
Conference_Titel :
Decision and Control, 1991., Proceedings of the 30th IEEE Conference on
Conference_Location :
Brighton
Print_ISBN :
0-7803-0450-0
DOI :
10.1109/CDC.1991.261860
