Markov Chains
Gibbs Fields, Monte Carlo Simulation and Queues
2nd Edition
Published on 24. May 2021
Book
Paperback/Softback
XVI, 557 pages
978-3-030-45984-0 (ISBN)
Description
Primarily an introduction to the theory of stochastic processes at the undergraduate or beginning graduate level, the primary objective of this book is to initiate students in the art of stochastic modelling. However it is motivated by significant applications and progressively brings the student to the borders of contemporary research. Examples are from a wide range of domains, including operations research and electrical engineering. Researchers and students in these areas as well as in physics, biology and the social sciences will find this book of interest.
More details
Product info
Book
Series
Edition
2nd ed. 2020
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Edition type
Revised edition
Illustrations
93
93 s/w Abbildungen
XVI, 557 p. 93 illus.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 31 mm
Weight
861 gr
ISBN-13
978-3-030-45984-0 (9783030459840)
DOI
10.1007/978-3-030-45982-6
Schweitzer Classification
Other editions
Additional editions
Book
05/2020
2nd Edition
Springer
€64.19
Shipment within 7-9 days
Person
Pierre Brémaud graduated from the École Polytechnique and obtained his Doctorate in Mathematics from the University of Paris VI and his PhD from the department of Electrical Engineering and Computer Science at the University of California, Berkeley. He is a major contributor to the theory of stochastic processes and their applications, and has authored or co-authored several reference books and textbooks.
Content
Preface.- 1 Probability Review.- 2 Discrete-Time Markov Chains.- 3 Recurrence and Ergodicity.- 4 Long-Run Behavior.- 5 Discrete-Time Renewal Theory.- 6 Absorption and Passage Times.- 7 Lyapunov Functions and Martingales.- 8 Random Walks on Graphs.- 9 Convergence Rates.- 10 Markov Fields on Graphs.- 11 Monte Carlo Markov Chains.- 12 Non-homogeneous Markov Chains.- 13 Continuous-Time Markov Chains.- 14 Markovian Queueing Theory.- Appendices.- Bibliography.- Index.