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    Risk-sensitive Maximum Likelihood sequence estimation.


    Elliott, R. J. and Moore, J. 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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