Markov Chains
Markov Chains
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马尔可夫链
DOI：
10.1007/978-3-030-45982-6
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
P. Brémaud
中科院分区：
文献类型：
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作者：
P. Brémaud
本书讨论了马尔可夫链的理论和应用。作者研究了离散时间和连续时间链和连接的主题，如有限吉布斯场，非齐次马尔可夫链，离散时间再生过程，蒙特卡罗模拟，模拟退火，排队网络也在这个可访问和自包含的文本中开发。本文首先介绍了随机过程的理论在本科或研究生开始水平。它的主要目标是引导学生学习随机建模的艺术。处理是数学的，有定义、定理、证明和一些课堂例子，帮助学生充分掌握主要结果的内容。在每一章的末尾都提出了不同难度的问题。文本的动机是显著的应用，并逐步将学生带到当代研究的边界。运筹学、电气工程、物理学、生物学和社会科学的学生和研究人员都会对这本书感兴趣。
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.