DocumentCode
300439
Title
On discrete hidden Markov state estimation
Author
Yang, Chun
Author_Institution
Signal & Syst. Technol., Seattle, WA, USA
Volume
1
fYear
1995
fDate
21-23 Jun 1995
Firstpage
12
Abstract
Hidden Markov models can be used to describe the behavior of a class of dynamic systems that are subject to abrupt changes. Since the Markov state is “hidden” and can only be observed through imperfect observations, its estimation is of practical importance for control and prediction. In this paper, a unified framework is established within which a comparative study of various hidden state estimation filters based on discrete-valued observations is presented
Keywords
filtering theory; hidden Markov models; state estimation; control; discrete hidden Markov state estimation; discrete-valued observations; hidden Markov models; imperfect observations; prediction; state estimation filters; Control systems; Filters; Hidden Markov models; Hydrogen; Manufacturing automation; State estimation; Target recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, Proceedings of the 1995
Conference_Location
Seattle, WA
Print_ISBN
0-7803-2445-5
Type
conf
DOI
10.1109/ACC.1995.529197
Filename
529197
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