Discrete probability models and methods : probability on graphs and trees, Markov chains and random fields, entropy and coding
- 作者： Bremaud, Pierre, author.
- 其他作者：
- 其他題名：
- Probability theory and stochastic modelling ;
- 出版： Cham : Springer International Publishing :Imprint: Springer
- 叢書名： Probability theory and stochastic modelling,volume 78
- 主題： Probabilities--Data processing. , Computer science--Mathematics. , Mathematics. , Probability Theory and Stochastic Processes. , Probability and Statistics in Computer Science. , Graph Theory. , Coding and Information Theory. , Computer Communication Networks.
- ISBN： 9783319434766 (electronic bk.) 、 9783319434759 (paper)
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FIND@SFXID:
CGU
- 資料類型: 電子書
- 內容註: Introduction -- 1.Events and probability -- 2.Random variables -- 3.Bounds and inequalities -- 4.Almost-sure convergence -- 5.Coupling and the variation distance -- 6.The probabilistic method -- 7.Codes and trees -- 8.Markov chains -- 9.Branching trees -- 10.Markov fields on graphs -- 11.Random graphs -- 12.Recurrence of Markov chains -- 13.Random walks on graphs -- 14.Asymptotic behaviour of Markov chains -- 15.Monte Carlo sampling -- 16. Convergence rates -- Appendix -- Bibliography.
- 摘要註: The emphasis in this book is placed on general models (Markov chains, random fields, random graphs), universal methods (the probabilistic method, the coupling method, the Stein-Chen method, martingale methods, the method of types) and versatile tools (Chernoff's bound, Hoeffding's inequality, Holley's inequality) whose domain of application extends far beyond the present text. Although the examples treated in the book relate to the possible applications, in the communication and computing sciences, in operations research and in physics, this book is in the first instance concerned with theory. The level of the book is that of a beginning graduate course. It is self-contained, the prerequisites consisting merely of basic calculus (series) and basic linear algebra (matrices) The reader is not assumed to be trained in probability since the first chapters give in considerable detail the background necessary to understand the rest of the book.
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讀者標籤：
- 系統號： 005382730 | 機讀編目格式
館藏資訊
The emphasis in this book is placed on general models (Markov chains, random fields, random graphs), universal methods (the probabilistic method, the coupling method, the Stein-Chen method, martingale methods, the method of types) and versatile tools (Chernoff's bound, Hoeffding's inequality, Holley's inequality) whose domain of application extends far beyond the present text. Although the examples treated in the book relate to the possible applications, in the communication and computing sciences, in operations research and in physics, this book is in the first instance concerned with theory. The level of the book is that of a beginning graduate course. It is self-contained, the prerequisites consisting merely of basic calculus (series) and basic linear algebra (matrices). The reader is not assumed to be trained in probability since the first chapters give in considerable detail the background necessary to understand the rest of the book.