概率論和隨機過程（第2版） [Theory of Probability and Random Processes] pdf epub mobi txt 電子書 下載 2025

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[美] 凱羅勒夫（Leonid B.Koralov） 著

齣版社： 世界圖書齣版公司

ISBN：9787510044106

版次：2

商品編碼：11124548

包裝：平裝

外文名稱：Theory of Probability and Random Processes

開本：24開

齣版時間：2012-06-01

用紙：膠版紙

頁數：353

正文語種：英文

內容簡介

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）.

內頁插圖

目錄

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

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評分☆☆☆☆☆

原著就是高質量的作品，影印版很好

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一個隨機過程的概率分配通常是由指定它的隨機變量的聯閤分布來給定的，這些聯閤分布以及由它們誘導齣來的概率可以解釋為樣本函數的性質的概率。例如，如果to是一個參數值，樣本函數在to取正值的概率是隨機變量x(to)有正值的概率。在這個水平上的基本定理：任意指定的自身相容的聯閤概率分布對應一隨機過程。

評分☆☆☆☆☆

這個概率論我本科的時候沒學好，現在補一補

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　　 目次：全書其有四部分，新增加瞭5章，總共17章。（一）集閤論、實數和微積分：集閤論；實數體係和微積分。（二）測度、積分和微分：實綫上的勒貝格理論；實綫上的勒貝格積分；測度和乘積測度的擴展；概率論基礎；微分和絕對連續；單測度和復測度。（三）拓撲、度量和正規空間：拓撲、度量和正規空間基本理論；可分離性和緊性；完全空間和緊空間；希爾伯特空間和經典巴拿赫空間；正規空間和局部凸空間。（四）調和分析、動力係統和hausdorff側都：調和分析基礎；可測動力係統；hausdorff測度和分形。

評分☆☆☆☆☆

好書，值得一看，價格公道，裝幀精美

評分☆☆☆☆☆

本書為英文原版內容不錯，對學習數學有很大幫助，是本不錯的工具書，同時有助於提高英語水平，但是發貨的包裝對書的保護嚴重不足。

評分☆☆☆☆☆

還是比較好的一本書，順便學習英語吧

評分☆☆☆☆☆

剛收到書，還沒有看，希望能讀完吧，大傢的評價都還不錯。