DocumentCode
336870
Title
A framework for mixed estimation of hidden Markov models
Author
Dey, Subhrakanti ; Marcus, Steven I.
Author_Institution
Inst. for Syst. Res., Maryland Univ., College Park, MD, USA
Volume
3
fYear
1998
fDate
1998
Firstpage
3473
Abstract
In this paper, we present a framework for a mixed estimation scheme for hidden Markov models (HMM). A robust estimation scheme is first presented using the minimax method that minimizes a worst case cost for HMMs with bounded uncertainties. Then we present a mixed estimation scheme that minimizes a risk-neutral cost with a constraint on the worst-case cost. Some simulation results are also presented to compare these different estimation schemes in cases of uncertainties in the noise model
Keywords
estimation theory; hidden Markov models; minimax techniques; probability; state estimation; bounded uncertainty; hidden Markov models; minimax method; probability; robust estimation; state estimation; worst case cost; Biomedical signal processing; Costs; Educational institutions; Hidden Markov models; Noise robustness; Probability; Signal processing algorithms; State estimation; Stochastic resonance; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1998. Proceedings of the 37th IEEE Conference on
Conference_Location
Tampa, FL
ISSN
0191-2216
Print_ISBN
0-7803-4394-8
Type
conf
DOI
10.1109/CDC.1998.758243
Filename
758243
Link To Document