随机积分导论-第2版 本书特色

　　《随机积分导论（第2版）（英文版）》是一部可读性很强的讲述随机积分和随机微分方程的入门教程。将基本理论和应用巧妙结合，非常适合学习过概率论知识的研究生，学习随机积分。运用现代方法，随机积分的定义是为了可料被积函数和局部鞅，紧接着是连续鞅的变分公式ito变化。《随机积分导论（第2版）（英文版）》包括在布朗运动的描述、鞅的hermite多项式、feynman-kac泛函和schrodinger方程。这是第二版，讨论了cameron-martin-giranov变换，并且在*后一章引入随机微分方程和一些学生用的练习。

随机积分导论-第2版 目录

preface
preface to the first edition
abbreviations and symbols
1. preliminaries
1.1 notations and conventions
1.2 measurability, lp spaces and monotone class theorems
1.3 functions of bounded variation and stieltjes integrals
1.4 probability space, random variables, filtration
1.5 convergence, conditioning
1.6 stochastic processes
1.7 optional times
1.8 two canonical processes
1.9 martingales
1.10 local martingales
1.11 exercises

2. definition of the stochastic integral
2.1 introduction
2.2 predictable sets and processes
2.3 stochastic intervals
2.4 measure on the predictable sets
2.5 definition of the stochastic integral
2.6 extension to local integrators and integrands
2.7 substitution formula
2.8 a sufficient condition for extendability of hz
2.9 exercises

3. extension of the predictable integrands
3.1 introduction
3.2 relationship between p, o, and adapted processes
3.3 extension of the integrands
3.4 a historical note
3.5 exercises

4. quadratic variation process
4.1 introduction
4.2 definition and characterization of quadratic variation
4.3 properties of quadratic variation for an l2-wartingale
4.4 direct definition of μm
4.5 decomposition of （m）2
4.6 a limit theorem
4.7 exercises

5. the ito formula
5.1 introduction
5.2 one-dimensional it5 formula
5.3 mutual variation process
5.4 multi-dimensional it5 formula
5.5 exercises
……
6. applications of the ito formula
7. local time and tanaka's formula
8. reflected brownian motions
9. generalized fro formula,change of time and measure
10. stochastic differential equations

自然科学 数学 微积分

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