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Topics in the Constructive Theory of Countable Markov Chains (Hardcover, New): G. Fayolle, V.A. Malyshev, M. V. Menshikov Topics in the Constructive Theory of Countable Markov Chains (Hardcover, New)
G. Fayolle, V.A. Malyshev, M. V. Menshikov
R3,385 Discovery Miles 33 850 Ships in 12 - 19 working days

Markov chains are an important idea, related to random walks, which crops up widely in applied stochastic analysis. They are used for such applications as performance modelling and evaluation of computer networks, queuing networks and telecommunication systems. The point of this book is to provide methods, based on the construction of Lyapunov functions, of determining when a Markov chain is ergodic, null recurrent or transient. These methods, which are, on the whole, original and new, can also be extended to the study of questions of stability. Of particular concern are reflected random walks and reflected Brownian motion. The authors provide not only a self-contained introduction to the theory, but also details of how the required Lyapunov functions are constructed in various situations.

Modelling and Performance Evaluation Methodology - Proceedings of the International Seminar, Paris, France, January 24-26, 1983... Modelling and Performance Evaluation Methodology - Proceedings of the International Seminar, Paris, France, January 24-26, 1983 (English, French, Paperback)
Francois Baccelli, G. Fayolle
R1,655 Discovery Miles 16 550 Ships in 10 - 15 working days
Topics in the Constructive Theory of Countable Markov Chains (Paperback): G. Fayolle, V.A. Malyshev, M. V. Menshikov Topics in the Constructive Theory of Countable Markov Chains (Paperback)
G. Fayolle, V.A. Malyshev, M. V. Menshikov
R1,366 Discovery Miles 13 660 Ships in 12 - 19 working days

Markov chains are an important idea, related to random walks, which crops up widely in applied stochastic analysis. They are used for example in performance modeling and evaluation of computer networks, queuing networks, and telecommunication systems. The main point of the present book is to provide methods, based on the construction of Lyapunov functions, of determining when a Markov chain is ergodic, null recurrent, or transient. These methods, which are on the whole original and new, can also be extended to the study of questions of stability. Of particular concern are reflected random walks and reflected Brownian motion. Here, the authors provide a self-contained introduction to the theory and details of how the required Lyapunov functions are constructed in various situations.

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