Elliott, R. J. and Moore, John B. and Dey, Subhrakanti (1996) Risk-sensitive Maximum Likelihood sequence estimation. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 43 (9).

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Abstract

In this brief, we consider risk-sensitive Maximum Likelihood sequence estimation for hidden Markov models with finite-discrete states. An algorithm is proposed which is essentially a risk-sensitive variation of the Viterbi algorithm. Simulation studies show that the risk-sensitive algorithm is more robust to uncertainties in the transition probability matrix of the Markov chain. Similar estimation results are also obtained for continuous-range models.

Item Type:	Article
Keywords:	Risk-sensitive; Maximum Likelihood; sequence estimation;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering
Item ID:	12734
Identification Number:	https://doi.org/10.1109/81.536754
Depositing User:	Subhrakanti Dey
Date Deposited:	14 Apr 2020 10:33
Journal or Publication Title:	IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
Publisher:	IEEE
Refereed:	Yes
URI:

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