Introduction to Hidden Semi-Markov Models
eBook - PDF

Introduction to Hidden Semi-Markov Models

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Introduction to Hidden Semi-Markov Models

About this book

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 This book contains new results and previously unpublished material not available elsewhere.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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Yes, you can access Introduction to Hidden Semi-Markov Models by John van der Hoek,Robert J. Elliott in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Series page
  3. Title page
  4. Copyright page
  5. Contents
  6. Preface
  7. 1 Observed Markov Chains
  8. 2 Estimation of an Observed Markov Chain
  9. 3 Hidden Markov Models
  10. 4 Filters and Smoothers
  11. 5 The Viterbi Algorithm
  12. 6 The EM Algorithm
  13. 7 A New Markov Chain Model
  14. 8 Semi-Markov Models
  15. 9 Hidden Semi-Markov Models
  16. 10 Filters for Hidden Semi-Markov Models
  17. Appendix A Higher-Order Chains
  18. Appendix B An Example of a Second-Order Chain
  19. Appendix C A Conditional Bayes Theorem
  20. Appendix D On Conditional Expectations
  21. Appendix E Some Molecular Biology
  22. Appendix F Earlier Applications of Hidden Markov Chain Models
  23. References
  24. Index