Markov chains and hidden Markov chains have applications in many
areas of engineering and genomics. This book provides a basic
introduction to the subject by first developing the theory of
Markov processes in an elementary discrete time, finite state
framework suitable for senior undergraduates and graduates. The
authors then introduce semi-Markov chains and hidden semi-Markov
chains, before developing related estimation and filtering results.
Genomics applications are modelled by discrete observations of
these hidden semi-Markov chains. This book contains new results and
previously unpublished material not available elsewhere. The
approach is rigorous and focused on applications.
General
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