Dey, Subhrakanti and Marcus, Steven I. (1998) A framework for mixed estimation of hidden Markov models. In: Proceedings of the 37th IEEE Conference on Decision and Control. IEEE, pp. 3473-3478. ISBN 0780343948

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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.

Item Type:	Book Section
Additional Information:	Cite as: S. Dey and S. I. Marcus, "A framework for mixed estimation of hidden Markov models," Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171), 1998, pp. 3473-3478 vol.3, doi: 10.1109/CDC.1998.758243.
Keywords:	Hidden Markov models; State estimation; Costs; Uncertainty; Signal processing algorithms; Noise robustness; Educational institutions; Stochastic resonance; Biomedical signal processing; Probability;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	14435
Identification Number:	https://doi.org/10.1109/CDC.1998.758243
Depositing User:	Subhrakanti Dey
Date Deposited:	18 May 2021 15:07
Publisher:	IEEE
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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