Hybrid filters modulated by Markov chains with two-time scales

Author

Yin, G. ; Dey, S.

Author_Institution

Dept. of Math., Wayne State Univ., Detroit, MI, USA

Volume

3

fYear

2002

fDate

10-13 Dec. 2002

Firstpage

3573

Abstract

We consider a class of hybrid filtering problems in discrete-time. The main feature is that the system is modulated by a Markov chain. Our main effort is to reduce the complexity of the underlying problems. Consider the case that the Markov chain has a large state space. Then the solution of the problem relies on solving a large number of filtering equations. By using the hierarchical structure of the system, we show that a reduced system of filtering equations can be obtained by aggregating the states of each recurrent class into one state. Extensions to inclusion of transient states and nonstationary cases are also treated.

Keywords

Markov processes; computational complexity; convergence; discrete time systems; filtering theory; matrix algebra; Markov chains; complexity reduction; discrete-time; filtering equations; hybrid filters; near complete decomposability; two-time scales; weak convergence; Equations; Filtering; Filters; Hidden Markov models; Speech recognition; State-space methods; Target recognition; Target tracking; Telecommunications; Traffic control;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2002, Proceedings of the 41st IEEE Conference on

ISSN

0191-2216

Print_ISBN

0-7803-7516-5

Type

conf

DOI

10.1109/CDC.2002.1184431

Filename

1184431