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Markov Chains and Stochastic Stability

  • Sean P. Meyn
  • Richard L. Tweedie

Part of the Communications and Control Engineering Series book series (CCE)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Communication and Regeneration

    1. Front Matter
      Pages 1-1
    2. Sean P. Meyn, Richard L. Tweedie
      Pages 3-22
    3. Sean P. Meyn, Richard L. Tweedie
      Pages 23-53
    4. Sean P. Meyn, Richard L. Tweedie
      Pages 54-79
    5. Sean P. Meyn, Richard L. Tweedie
      Pages 80-99
    6. Sean P. Meyn, Richard L. Tweedie
      Pages 100-125
    7. Sean P. Meyn, Richard L. Tweedie
      Pages 126-148
    8. Sean P. Meyn, Richard L. Tweedie
      Pages 149-169
  3. Stability Structures

    1. Front Matter
      Pages 171-171
    2. Sean P. Meyn, Richard L. Tweedie
      Pages 173-199
    3. Sean P. Meyn, Richard L. Tweedie
      Pages 200-228
    4. Sean P. Meyn, Richard L. Tweedie
      Pages 229-254
    5. Sean P. Meyn, Richard L. Tweedie
      Pages 255-284
    6. Sean P. Meyn, Richard L. Tweedie
      Pages 285-305
  4. Convergence

    1. Front Matter
      Pages 307-307
    2. Sean P. Meyn, Richard L. Tweedie
      Pages 309-329
    3. Sean P. Meyn, Richard L. Tweedie
      Pages 330-353
    4. Sean P. Meyn, Richard L. Tweedie
      Pages 354-381
    5. Sean P. Meyn, Richard L. Tweedie
      Pages 382-409
    6. Sean P. Meyn, Richard L. Tweedie
      Pages 410-445
    7. Sean P. Meyn, Richard L. Tweedie
      Pages 446-464
    8. Sean P. Meyn, Richard L. Tweedie
      Pages 465-491
  5. Back Matter
    Pages 493-552

About this book

Introduction

Markov Chains and Stochastic Stability is part of the Communications and Control Engineering Series (CCES) edited by Professors B.W. Dickinson, E.D. Sontag, M. Thoma, A. Fettweis, J.L. Massey and J.W. Modestino. The area of Markov chain theory and application has matured over the past 20 years into something more accessible and complete. It is of increasing interest and importance. This publication deals with the action of Markov chains on general state spaces. It discusses the theories and the use to be gained, concentrating on the areas of engineering, operations research and control theory. Throughout, the theme of stochastic stability and the search for practical methods of verifying such stability, provide a new and powerful technique. This does not only affect applications but also the development of the theory itself. The impact of the theory on specific models is discussed in detail, in order to provide examples as well as to demonstrate the importance of these models. Markov Chains and Stochastic Stability can be used as a textbook on applied Markov chain theory, provided that one concentrates on the main aspects only. It is also of benefit to graduate students with a standard background in countable space stochastic models. Finally, the book can serve as a research resource and active tool for practitioners.

Keywords

Drift Markov Markov chain Markov model Symbol Transit calculus communication control control engineering control theory model operations research probability theory stability

Authors and affiliations

  • Sean P. Meyn
    • 1
  • Richard L. Tweedie
    • 2
  1. 1.Coordinated Science Laboratory and the Department of Electrical and Computer EngineeringUniversity of IllinoisUrbanaUSA
  2. 2.Department of StatisticsColorado State UniversityFort CollinsUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4471-3267-7
  • Copyright Information Springer-Verlag London 1993
  • Publisher Name Springer, London
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4471-3269-1
  • Online ISBN 978-1-4471-3267-7
  • Series Print ISSN 0178-5354
  • Buy this book on publisher's site