Markov Chains: Gibbs Fields, Monte Carlo Simulation and Queues

This book discusses both the theory and applications of Markov chains. The author studies both discrete-time and continuous-time chains and connected topics such as finite Gibbs fields, non-homogeneous Markov chains, discrete time regenerative processes, Monte Carlo simulation, simulated annealing, and queueing networks are also developed in this accessible and self-contained text. The text is firstly an introduction to the theory of stochastic processes at the undergraduate or beginning graduate level. Its primary objective is to initiate the student to the art of stochastic modelling. The treatment is mathematical, with definitions, theorems, proofs and a number of classroom examples which help the student to fully grasp the content of the main results. Problems of varying difficulty are proposed at the close of each chapter. The text is motivated by significant applications and progressively brings the student to the borders of contemporary research. Students and researchers in operations research and electrical engineering as well as in physics, biology and the social sciences will find this book of interest.

Author: Pierre Brémaud
Publisher: Springer
Published: 05/24/2020
Pages: 557
Binding Type: Hardcover
Weight: 2.15lbs
Size: 9.21h x 6.14w x 1.25d
ISBN13: 9783030459819
ISBN10: 3030459810
BISAC Categories:
- Mathematics | Probability & Statistics | General
- Business & Economics | Operations Research
- Technology & Engineering | Electrical

About the Author
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.