2011Journal of Nanjing University of Posts and TelecommunicationsRequires access

Parametric Estimation of Nth-order Hidden Markov Models

Youguo Wang

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Abstract

Definition and structure are given of nth-order hidden Markov models.Forward-backward algorithm and Baum-Welch algorithm of the models are studied based on the traditional second-order hidden Markov model.Parameter estimation equations for the models are derived for the cases of both single and multiple observation sequence training.

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Definition and structure are given of nth-order hidden Markov models.Forward-backward algorithm and Baum-Welch algorithm of the models are studied based on the traditional second-order hidden Markov model.Parameter estimation equations for the models are derived for the cases of both single and multiple observation sequence training.

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Available abstract

Definition and structure are given of nth-order hidden Markov models.Forward-backward algorithm and Baum-Welch algorithm of the models are studied based on the traditional second-order hidden Markov model.Parameter estimation equations for the models are derived for the cases of both single and multiple observation sequence training.

Key concepts: Hidden Markov model, Markov model, Markov chain, Maximum-entropy Markov model, Hidden semi-Markov model, Forward algorithm, Sequence (biology), Parametric statistics

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