金融随机分析的经典教材，全书分上下两卷。第一卷主要包括随机分析的基础性知识以及离散时问模型，利用较简单的离散时间二叉树模型给出了无套利期权定价方法；虽只用到简单的数学，但其中涉及的风险中性定价的概念卜分深刻。第二卷主要介绍连续时问模型及其在金融学中的应用；其中包含了较为实际的、具有很强操作性的定量经济学内容，同时也包含了较为完整的随机分析理论。全书各章均有评注和习题。

随机系统分析与建模Modeling and Analysis of Stochastic Systems很全面

本书的目的是为解决由科学，工程和数学金融领域的随机微分方程模型提出的问题提供有益的理解。 通常，这些问题需要使用数值方法来获得解决方案。

机器人状态估计理论经典

《金融随机分析(共2卷)》是《金融随机分析》的第2卷，《金融随机分析》全书共分两卷。第一卷主要包括随机分析的基础性知识以及离散时问模型，利用较简单的离散时间二叉树模型给出了无套利期权定价方法；虽只用到简单的数学，但其中涉及的风险中性定价的概念卜分深刻。第二卷主要介绍连续时问模型及其在金融学中的应用；其中包含了较为实际的、具有很强操作性的定量经济学内容，同时也包含了较为完整的随机分析理论。全书各章均有评注和习题。

Covering point process theory, random geometric graphs and coverage processes, this rigorous introduction to stochastic geometry will enable you to obtain powerful, general estimates and bounds of wireless network performance and make good design choices for future wireless architectures and protocols that efficiently manage interference effects. Practical engineering applications are integrated with mathematical theory, with an understanding of probability the only prerequisite. At the same time, stochastic geometry is connected to percolation theory and the theory of random geometric graphs and accompanied by a brief introduction to the R statistical computing language. Combining theory and hands-on analytical techniques with practical examples and exercises, this is a comprehensive guide to the spatial stochastic models essential for modelling and analysis of wireless network performance.

Within the mathematical programming community, it is common to split the field into topics such as linear programming, nonlinear programming, network flows, integer and combinatorial optimization, and, finally, stochastic programming. Convenient as that may be, it is conceptually inappropriate. It puts forward the idea that stochastic programming is distinct from integer programming the same way that linear programming is distinct from nonlinear programming. The counterpart of stochastic programming is, of course, deterministic programming. We have stochastic and deterministic linear programming, deterministic and stochastic network flow problems, and so on. Although this book mostly covers stochastic linear programming (since that is the best developed topic), we also discuss stochastic nonlinear programming, integer programming and network flows.

美国Polytechnic University的Athanasios Papoulis教授的经典教材配套习题答案

不错的随机过程专业教程，全面地讲述随机过程的相关基础知识。

随即过程滤波的经典教材，Jazwinski的代表作，欢迎大家下载