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＜電子ブック＞
Markov Chains : Gibbs Fields, Monte Carlo Simulation, and Queues / by Pierre Bremaud
(Texts in Applied Mathematics. ISSN:21969949 ; 31)

版	1st ed. 1999.
出版者	New York, NY : Springer New York : Imprint: Springer
出版年	1999
本文言語	英語
大きさ	XVIII, 444 p : online resource
冊子体	Markov chains : Gibbs fields, Monte Carlo simulation and queues / Pierre Brémaud
著者標目	*Bremaud, Pierre author SpringerLink (Online service)
件　名	LCSH:Probabilities LCSH:Operations research LCSH:Electrical engineering FREE:Probability Theory FREE:Operations Research and Decision Theory FREE:Electrical and Electronic Engineering
一般注記	1 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 In 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 Accessibility summary: This PDF is not accessible. It is based on scanned pages and does not support features such as screen reader compatibility or described non-text content (images, graphs etc). However, it likely supports searchable and selectable text based on OCR (Optical Character Recognition). Users with accessibility needs may not be able to use this content effectively. Please contact us at accessibilitysupport@springernature.com if you require assistance or an alternative format Inaccessible, or known limited accessibility No reading system accessibility options actively disabled Publisher contact for further accessibility information: accessibilitysupport@springernature.com HTTP:URL=https://doi.org/10.1007/978-1-4757-3124-8

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