Stochastic Geometry and Wireless Networks Iⅈ 第一卷以及第二卷

《ImageProcessingandAnalysis》将现代数学与现代图像处理中最先进的方法联系起来，组织成一个连贯的逻辑结构。作者通过它们连接到傅里叶和光谱分析中的少数共同线程，揭示了传统图像处理的原理，从而整合了现代图像处理方法的多样性。可以说，这本书是全面而且综合的，它涵盖了当代图像分析和处理中的4个最强大的数学工具类，同时也探索了它们的内在连接和集成。

一部较好地关于，动态模型估计的书籍。希望能够帮助到需要的朋友。

Edward P.C. 随机过程导论，英文版

Stochastic calculus for finance II

This text is written to teach the theory of Lyapunov drift and Lyapunov optimization for stochastic network optimization. It assumes only that the reader is familiar with basic probability concepts (such as expectations and the law of large numbers). Familiarity with Markov chains and with standard (non-stochastic) optimization is useful but not required. A variety of examples and simulation results are given to illustrate the main concepts. Diverse problem set questions (several with example solutions) are also given. These questions and examples were developed over several years for use in the stochastic network optimization course taught by the author. They include topics of wireless opportunistic scheduling, multi-hop routing, network coding for maximum throughput, distortion-aware data compression, energy-constrained and delay-constrained queueing, dynamic decision making for maximum profit, and more.

stochastic network optimization with application to communication Michael J. N 著 2010版

Stochastic Processes and Filtering Theory.pdf

A wireless communication network can be viewed as a collection of nodes, located in some domain, which can in turn be transmitters or receivers (depending on the network considered, nodes may be mobile users, base stations in a cellular network, access points of a WiFi mesh etc.). At a given time, several nodes transmit simultaneously, each toward its own receiver. Each transmitter–receiver pair requires its own wireless link. The signal received from the link transmitter may be jammed by the signals received from the other transmitters. Even in the simplest model where the signal power radiated from a point decays in an isotropic way with Euclidean distance, the geometry of the locations of the nodes plays a key role since it determines the signal to interference and noise ratio (SINR) at each receiver and hence the possibility of establishing simultaneously this collection of links at a given bit rate. The interference seen by a receiver is the sum of the signal powers received from all transmitters, except its own transmitter.

A wireless communication network can be viewed as a collection of nodes, located in some domain, which can in turn be transmitters or receivers (depending on the network considered, nodes may be mobile users, base stations in a cellular network, access points of a WiFi mesh etc.). At a given time, several nodes transmit simultaneously, each toward its own receiver. Each transmitter–receiver pair requires its own wireless link. The signal received from the link transmitter may be jammed by the signals received from the other transmitters. Even in the simplest model where the signal power radiated from a point decays in an isotropic way with Euclidean distance, the geometry of the locations of the nodes plays a key role since it determines the signal to interference and noise ratio (SINR) at each receiver and hence the possibility of establishing simultaneously this collection of links at a given bit rate. The interference seen by a receiver is the sum of the signal powers received from all transmitters, except its own transmitter.