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OverviewIn this book, the author begins with the elementary theory of Markov chains and very progressively brings the reader to the more advanced topics. He gives a useful review of probability that makes the book self-contained, and provides an appendix with detailed proofs of all the prerequisites from calculus, algebra, and number theory. A number of carefully chosen problems of varying difficulty are proposed at the close of each chapter, and the mathematics are slowly and carefully developed, in order to make self-study easier. The author treats the classic topics of Markov chain theory, both in discrete time and continuous time, as well as the connected topics such as finite Gibbs fields, nonhomogeneous Markov chains, discrete- time regenerative processes, Monte Carlo simulation, simulated annealing, and queuing theory. The result is an up-to-date textbook on stochastic processes. Students and researchers in operations research and electrical engineering, as well as in physics and biology, will find it very accessible and relevant. Full Product DetailsAuthor: Pierre BremaudPublisher: Springer-Verlag New York Inc. Imprint: Springer-Verlag New York Inc. Edition: 1st ed. 1999. Corr. 2nd printing 2001 Volume: 31 Dimensions: Width: 16.00cm , Height: 2.50cm , Length: 24.00cm Weight: 1.102kg ISBN: 9780387985091ISBN 10: 0387985093 Pages: 444 Publication Date: 11 May 1999 Audience: College/higher education , Professional and scholarly , Undergraduate , Postgraduate, Research & Scholarly Replaced By: 9783030459819 Format: Hardback Publisher's Status: Active Availability: Awaiting stock ![]() The supplier is currently out of stock of this item. It will be ordered for you and placed on backorder. Once it does come back in stock, we will ship it out for you. Table of Contents1 Probability Review.- 2 Discrete-Time Markov Models.- 3 Recurrence and Ergodicity.- 4 Long Run Behavior.- 5 Lyapunov Functions and Martingales.- 6 Eigenvalues and Nonhomogeneous Markov Chains.- 7 Gibbs Fields and Monte Carlo Simulation.- 8 Continuous-Time Markov Models.- 9 Poisson Calculus and Queues.- 1 Number Theory and Calculus.- 1.1 Greatest Common Divisor.- 1.2 Abel’s Theorem.- 1.3 Lebesgue’s Theorems for Series.- 1.4 Infinite Products.- 1.5 Tychonov’s Theorem.- 1.6 Subadditive Functions.- 2 Linear Algebra.- 2.1 Eigenvalues and Eigenvectors.- 2.2 Exponential of a Matrix.- 2.3 Gershgorin’s Bound.- 3 Probability.- 3.1 Expectation Revisited.- 3.2 Lebesgue’s Theorems for Expectation.- Author Index.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |