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Introduction to hidden semi-Markov models / John van der Hoek (University of South Australia), Robert J. Elliott (University of Calgary).

By: Contributor(s): Material type: TextTextSeries: London Mathematical Society lecture note series ; 445.Publisher: Cambridge : Cambridge University Press, 2018Description: 1 online resource (x, 174 pages) : digital, PDF file(s)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781108377423 (ebook)
Subject(s): Additional physical formats: Print version: : No titleDDC classification:
  • 519.2/33 23
LOC classification:
  • QA274.7 .V356 2018
Online resources: Summary: 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 This book contains new results and previously unpublished material not available elsewhere.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.
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Title from publisher's bibliographic system (viewed on 12 Feb 2018).

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 This book contains new results and previously unpublished material not available elsewhere.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.

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