DocumentCode
3079917
Title
A 2-D realization theory for Markov chains
Author
Ramos, Jose A. ; Verriest, Erik I.
Author_Institution
United Technol. Opt. Syst., West Palm Beach, FL, USA
fYear
1990
fDate
5-7 Dec 1990
Firstpage
853
Abstract
The dynamics of time-homogeneous Markov chain models is studied from a state-space modeling point of view. It is shown that a Markov chain model can be embedded in a 2-D realization theory where Markov parameters correspond to higher-order transition probabilities. The implication of formulating a Markov chain model in this state-space domain is that many equivalent representations may exist, some of which may have better robustness properties. A modified Hankel approximation algorithm is presented which exactly matches all the Markov parameters. The algorithm is an extension of the 2-D harmonic retrieval algorithm of D.V.B. Rao et al. (1984)
Keywords
Markov processes; state-space methods; 2-D harmonic retrieval algorithm; 2-D realization theory; modified Hankel approximation algorithm; state-space modeling; time-homogeneous Markov chain models; Decision making; Differential equations; Dynamic programming; Hidden Markov models; History; Limit-cycles; Linear systems; Markov processes; Queueing analysis; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1990., Proceedings of the 29th IEEE Conference on
Conference_Location
Honolulu, HI
Type
conf
DOI
10.1109/CDC.1990.203709
Filename
203709
Link To Document