DocumentCode :
435168
Title :
Change detection of hidden Markov models
Author :
Gereneser, L. ; Molnár-Sáska, Gábor
Volume :
2
fYear :
2004
fDate :
14-17 Dec. 2004
Firstpage :
1754
Abstract :
Let θˆN denote the maximum-likelihood estimator of the true parameter θ* of a hidden Markov Model with fixed gain or forgetting rate λ. We establish an explicit formula for the error term θˆN - θ*. Using the representation of the error term we investigate the effect of parameter uncertainty on the performance of an adaptive encoding procedure. Using this result and ideas from the theory of stochastic complexity a change point detection method for HMM-s will be developed.
Keywords :
hidden Markov models; maximum likelihood estimation; stochastic processes; adaptive encoding procedure; change point detection; explicit formula; hidden Markov models; maximum-likelihood estimator; parameter uncertainty; stochastic complexity; Automation; Encoding; Estimation theory; Extraterrestrial measurements; Filters; Hidden Markov models; Maximum likelihood detection; State-space methods; Stochastic processes; Stochastic systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 2004. CDC. 43rd IEEE Conference on
ISSN :
0191-2216
Print_ISBN :
0-7803-8682-5
Type :
conf
DOI :
10.1109/CDC.2004.1430298
Filename :
1430298
Link To Document :
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