DocumentCode
2296167
Title
Improved estimation of the exponential stability of the predictive filter in hidden Markov models
Author
Gerencsér, László ; Molnár-Sáska, Gábor ; Michaletzky, György
Author_Institution
Inst. of Comput. & Autom., Hungarian Acad. of Sci., Budapest
fYear
2006
fDate
14-16 June 2006
Abstract
We consider finite state continuous read-out hidden Markov models. The exponential stability of the predictive filter was investigated by LeGland and Mevel (2000) when the transition probability matrix Q of the underlying Markov chain is primitive. We carry out further investigation of this exponential stability. Two important applications are derived: the strong approximation result has been extended for HMMs with primitive transition probability matrices and the validity of the recursive estimation of HMMs with primitive transition probability matrices has been shown
Keywords
asymptotic stability; filtering theory; hidden Markov models; predictive control; probability; exponential stability estimation; hidden Markov model; predictive filter; primitive transition probability matrix; recursive estimation; Automation; Filters; Hidden Markov models; Markov processes; Recursive estimation; Stability; State estimation; State-space methods; Stochastic systems; White noise;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2006
Conference_Location
Minneapolis, MN
Print_ISBN
1-4244-0209-3
Electronic_ISBN
1-4244-0209-3
Type
conf
DOI
10.1109/ACC.2006.1657544
Filename
1657544
Link To Document