Markov Chains and Stochastic Stability

Markov Chains and Stochastic Stability PDF Author: Sean Meyn
Publisher: Cambridge University Press
ISBN: 1139477978
Category : Mathematics
Languages : en
Pages : 595

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Book Description
Meyn and Tweedie is back! The bible on Markov chains in general state spaces has been brought up to date to reflect developments in the field since 1996 - many of them sparked by publication of the first edition. The pursuit of more efficient simulation algorithms for complex Markovian models, or algorithms for computation of optimal policies for controlled Markov models, has opened new directions for research on Markov chains. As a result, new applications have emerged across a wide range of topics including optimisation, statistics, and economics. New commentary and an epilogue by Sean Meyn summarise recent developments and references have been fully updated. This second edition reflects the same discipline and style that marked out the original and helped it to become a classic: proofs are rigorous and concise, the range of applications is broad and knowledgeable, and key ideas are accessible to practitioners with limited mathematical background.

Markov Chains and Stochastic Stability

Markov Chains and Stochastic Stability PDF Author: Sean P. Meyn
Publisher: Springer Science & Business Media
ISBN: 144713267X
Category : Technology & Engineering
Languages : en
Pages : 559

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Book Description
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.

Markov Chains and Stochastic Stability

Markov Chains and Stochastic Stability PDF Author: Sean Meyn
Publisher: Cambridge University Press
ISBN: 0521731828
Category : Mathematics
Languages : en
Pages : 623

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Book Description
New up-to-date edition of this influential classic on Markov chains in general state spaces. Proofs are rigorous and concise, the range of applications is broad and knowledgeable, and key ideas are accessible to practitioners with limited mathematical background. New commentary by Sean Meyn, including updated references, reflects developments since 1996.

Markov Chains and Stochastic Stability

Markov Chains and Stochastic Stability PDF Author: Sean P Meyn
Publisher:
ISBN: 9781447132684
Category :
Languages : en
Pages : 572

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Book Description


Markov Chains and Stochastic Stability

Markov Chains and Stochastic Stability PDF Author: Sean P. Meyn
Publisher:
ISBN:
Category :
Languages : en
Pages : 594

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Book Description


Strong Stable Markov Chains

Strong Stable Markov Chains PDF Author: N. V. Kartashov
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110917769
Category : Mathematics
Languages : en
Pages : 144

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Book Description
No detailed description available for "Strong Stable Markov Chains".

General Irreducible Markov Chains and Non-Negative Operators

General Irreducible Markov Chains and Non-Negative Operators PDF Author: Esa Nummelin
Publisher: Cambridge University Press
ISBN: 9780521604949
Category : Mathematics
Languages : en
Pages : 176

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Book Description
Presents the theory of general irreducible Markov chains and its connection to the Perron-Frobenius theory of nonnegative operators.

Continuous Time Markov Processes

Continuous Time Markov Processes PDF Author: Thomas Milton Liggett
Publisher: American Mathematical Soc.
ISBN: 0821849492
Category : Markov processes
Languages : en
Pages : 290

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Book Description
Markov processes are among the most important stochastic processes for both theory and applications. This book develops the general theory of these processes, and applies this theory to various special examples.

Topics in the Constructive Theory of Countable Markov Chains

Topics in the Constructive Theory of Countable Markov Chains PDF Author: G. Fayolle
Publisher: Cambridge University Press
ISBN: 9780521461979
Category : Mathematics
Languages : en
Pages : 184

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Book Description
Provides methods of analysing Markov chains based on Lyapunov functions.

Discrete-Time Markov Chains

Discrete-Time Markov Chains PDF Author: George Yin
Publisher: Springer Science & Business Media
ISBN: 9780387219486
Category : Business & Economics
Languages : en
Pages : 372

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Book Description
Focusing on discrete-time-scale Markov chains, the contents of this book are an outgrowth of some of the authors' recent research. The motivation stems from existing and emerging applications in optimization and control of complex hybrid Markovian systems in manufacturing, wireless communication, and financial engineering. Much effort in this book is devoted to designing system models arising from these applications, analyzing them via analytic and probabilistic techniques, and developing feasible computational algorithms so as to reduce the inherent complexity. This book presents results including asymptotic expansions of probability vectors, structural properties of occupation measures, exponential bounds, aggregation and decomposition and associated limit processes, and interface of discrete-time and continuous-time systems. One of the salient features is that it contains a diverse range of applications on filtering, estimation, control, optimization, and Markov decision processes, and financial engineering. This book will be an important reference for researchers in the areas of applied probability, control theory, operations research, as well as for practitioners who use optimization techniques. Part of the book can also be used in a graduate course of applied probability, stochastic processes, and applications.