概率论和随机过程（第2版） [Theory of Probability and Random Processes] 下载 mobi epub pdf 电子书 2025

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内容简介

This book is primarily based on a one-year course that has been taught for a number of years at Princeton University to advanced undergraduate and graduate students. During the last year a similar course has also been taught at the University of Maryland.
We would like to express our thanks to Ms. Sophie Lucas and Prof. Rafael Herrera who read the manuscript and suggested many corrections. We are particularly grateful to Prof. Boris Gurevich for making many important sug-gestions on both the mathematical content and style.
While writing this book， L. Koralov was supported by a National Sci-ence Foundation grant （DMS-0405152）. Y. Sinai was supported by a National Science Foundation grant （DMS-0600996）.

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目录

Part Ⅰ Probability Theory
1 Random Variables and Their Distributions
1.1 Spaces of Elementary Outcomes， a-Algebras， and Measures
1.2 Expectation and Variance of Random Variables on a Discrete Probability Space
1.3 Probability of a Union of Events
1.4 Equivalent Formulations of a-Additivity， Borel a-Algebras and Measurability
1.5 Distribution Functions and Densities
1.6 Problems
2 Sequences of Independent Trials
2.1 Law of Large Numbers and Applications
2.2 de Moivre-Laplace Limit Theorem and Applications
2.3 Poisson Limit Theorem.
2.4 Problems
3 Lebesgue Integral and Mathematical Expectation
3.1 Definition of the Lebesgue Integral
3.2 Induced Measures and Distribution Functions
3.3 Types of Measures and Distribution Functions
3.4 Remarks on the Construction of the Lebesgue Measure
3.5 Convergence of Functions， Their Integrals， and the Fubini Theorem
3.6 Signed Measures and the R，adon-Nikodym Theorem
3.7 Lp Spaces
3.8 Monte Carlo Method
3.9 Problems
4 Conditional Probabilities and Independence
4.1 Conditional Probabilities
4.2 Independence of Events， Algebras， and Random Variables
4.3
4.4 Problems
5 Markov Chains with a Finite Number of States
5.1 Stochastic Matrices
5.2 Markov Chains
5.3 Ergodic and Non-Ergodic Markov Chains
5.4 Law of Large Numbers and the Entropy of a Markov Chain
5.5 Products of Positive Matrices
5.6 General Markov Chains and the Doeblin Condition
5.7 Problems
6 Random Walks on the Lattice Zd
6.1 Recurrent and Transient R，andom Walks
6.2 Random Walk on Z and the Refiection Principle
6.3 Arcsine Law
6.4 Gambler's Ruin Problem
6.5 Problems
7 Laws of Larze Numbers
7.1 Definitions， the Borel-Cantelli Lemmas， and the Kolmogorov Inequality
7.2 Kolmogorov Theorems on the Strong Law of Large Numbers
7.3 Problems
8 Weak Converaence of Measures
8.1 Defnition of Weak Convergence
8.2 Weak Convergence and Distribution Functions
8.3 Weak Compactness， Tightness， and the Prokhorov Theorem
8.4 Problems
9 Characteristic Functions
9.1 Definition and Basic Properties
9.2 Characteristic Functions and Weak Convergence
9.3 Gaussian Random Vectors
9.4 Problems
10 Limit Theorems
10.1 Central Limit Theorem， the Lindeberg Condition
10.2 Local Limit Theorem
10.3 Central Limit Theorem and Renormalization GrOUD Theorv
10.4 Probabilities of Large Deviations
……
Part Ⅱ Random Processes
Index

前言/序言

概率论和随机过程（第2版） [Theory of Probability and Random Processes] 下载 mobi epub pdf txt 电子书 格式

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不错不错哦不错不错不错哦不错

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他是俄国科学院院士及美国文理科学院院士，他还是伦敦数学会名誉会员．他曾荣获Boltzmann金质奖章（1986）；Heinemann奖（1989）；Markov奖（1990）以及意大利Trieste国际理论物理中心Dirac奖章（1992）．1997年因“对统计力学中数学严格方法及动力系统的遍历理论以及它们在物理学中的应用所做的基本贡献”而获Wolf奖.他的工作是特别令人印象深刻的广度。 “[西奈半岛的工作除了其持久的影响在纯数学]已经起到了至关重要的作用创造动力的混乱，这已经被极其重要的物理学和非线性科学的发展在过去的三概念五年“。引用注意到压倒性的影响西奈半岛的工作，在过去的半个世纪中，包括他的250多篇研究论文，他的几本书。他监督了50多个博士生，其中许多人已成为在自己的权利领域的领导者。引用的结论是，“斯蒂尔被授予终身成就奖西奈承认所有这些成就。

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正版图书，内容经典，不错。

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原版的虽然看起来累些，但是描述的清楚

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研究随机过程的方法多种多样，主要可以分为两大类：一类是概率方法，其中用到轨道性质、停时和随机微分方程等；另一类是分析的方法，其中用到测度论、微分方程、半群理论、函数堆和希尔伯特空间等。实际研究中常常两种方法并用。另外组合方法和代数方法在某些特殊随机过程的研究中也有一定作用。研究的主要内容有：多指标随机过程、无穷质点与马尔可夫过程、概率

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很好的教材，赞一个！

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Sinal是统计物理学的数学问题的国际权威，特别是对遍历理论有突出贡献．他首次给出任意保测映射的不变量摘以严格定义．其后证明弹子运动的遍历性以及拟周期Schr?dinger方程的谱性质.

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不错是想要的书，比较经典

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一个实际的随机过程是任意一个受概率支配的过程，例子有：①看做是受孟德尔遗传学支配的群体的发展；②受分子碰撞影响的微观质点的布朗运动，或者是宏观空间的星体运动；③赌场中一系列的赌博；④公路一指定点汽车的通行。

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