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- W2732933420 abstract "In this paper, 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 state models." @default.
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- W2732933420 date "1996-06-01" @default.
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- W2732933420 title "Risk-Sensitive Maximum Likelihood Sequence Estimation" @default.
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- W2732933420 doi "https://doi.org/10.1016/s1474-6670(17)58410-4" @default.
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