十五年前，本书的第一版成为学习随机过程函数收敛的必备读物，这部科学巨著终于出第2版了，仍然延续了第1版的风格，但增加了不少新的知识，在厚度上的增加了将近50面。第1版面世后，可预测的一致胎紧性有了很大的进展，所以书中也做了全面的更新。本书仍然是学习随机过程的一本不可或缺的参考书。目次：随机过程一般概念；半鞅和独立增量过程的特征；鞅问题和测量改变；Hellinger过程、绝对连续和测度奇异性；绝对连续和奇异的可预测准则；近邻性、完全独立和变分收敛；Skorokhod拓扑和过程收敛；具有独立增量的过程收敛；具有独立增量过程的收敛；半鞅的收敛；极限定理、密度过程和近邻性。读者对象：数学专业的研究生、老师和相关的科研人员。
Chapter I. The General Theory of Stochastic Processes,
Semi*rtingales and Stochastic Integrals
1. Stochastic Basis, Stopping Times, Optionala-Field,Martingales
1a. Stochastic Basis
lb. Stopping Times
lc. The Optional a-Field
ld. The Localiz*ion Procedure
1e. Martingales
1f. The Discrete Case
2. Predi*able a-Field, Predi*able Times
2a. The Predi*able a-Field
2b. Predi*able Times
2c. Totally Inaccessible Stopping Times
2d. Predi*able Pro*e*ion
2e. The Discrete Case
3. Increasing Processes
3a. Basic Properties
3b. Do, b-Meyer Deposition and Compens*o*of IncreasingProcesses
3c. Lenglart Domin*ion Property
3d. The Discrete Case
4. Semi*rtingales and Stochastic Integrals
4a. Locally Square-Integrable Martingales
4b. Depositions of a Local Martingale
4c. Semi*rtingales
4d. Constru*ion of the Stochastic Integral
4e. Quadr*ic Vari*ion ofa Semi*rtingale and Ito's For*la
4f. Dol6ans-Dade Exponential For*la
4g. The Discrete Case
Chapter II. Chara*eristics of Semi*rtingales and Processes withIndependent Increments
1. Random Measures
1a. General Random Measures
lb. Integer-Valued Random Measures
1c. A Fundamental Example: Poisson Measures
1d. Stochastic Integral with Respe* to a Random Measure
2. Chara*eristics of Semi*rtingales
2a. Definition of the Chara*eristics
2b. Integrability and Chara*eristics
2c. A Canonical Represent*ion for Semi*rtingales
2d. Chara*eristics and Exponential For*la
3. Some Examples
3a. The Discrete Case
3b. More on the Discrete Case
3c. The 'One-Point' Point Process and Empirical Processes
4. Semi*rtingales with Independent Increments
4a. Wiener Processes
4b. Poisson Processes and Poisson Random Measures
4c. Processes with Independent Increments andSemi*rtingales
4d. Gaussian Martingales
5. Processes with Independent Increments
Which Are Not Semi*rtingales
5a. The Results
5b. The Proofs
6. Processes with Conditionally Independent Increments
7. Progressive Conditional Continuous PIIs
8. Semi*rtingales, Stochastic Exponential and StochasticLogarit*.
8a. More About Stochastic Exponential and StochasticLogarit*.
8b. Multiplic*ive Depositions andExponentially Special Semi*rtingales
Chapter III. Martingale Problems and Changes of Measures
1. Martingale Problems and Point Processes
1a. General Martingale Problems
1b. Martingale Problems and Random Measures
1c. Point Processes and Multivari*e Point Processes
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