Ross's classic bestseller, Introduction to Probability Models, has been used extensively by professionals and as the primary text for a first undergraduate course in applied probability. It provides an introduction to elementary probability theory and stochastic processes, and shows how probability theory can be applied to the study of phenomena in fields such as engineering, computer science, management science, the physical and social sciences, and operations research. With the addition of several new sections relating to actuaries, this text is highly recommended by the Society of Actuaries. A new section (3.7) on COMPOUND RANDOM VARIABLES, that can be used to establish a recursive formula for computing probability mass functions for a variety of common compounding distributions. A new section (4.11) on HIDDDEN MARKOV CHAINS, including the forward and backward approaches for computing the joint probability mass function of the signals, as well as the Viterbi algorithm for determining the most likely sequence of states. Simplified Approach for Analyzing Nonhomogeneous Poisson processes Additional results on queues relating to the (a) conditional distribution of the number found by an M/M/1 arrival who spends a time t in the system,; (b) inspection paradox for M/M/1 queues (c) M/G/1 queue with server breakdown Many new examples and exercises.

Introduction to probability and statistics 概率与统计的入门书籍，适合自学

Probability+and+Statistics+for+Computer+Scientists

PROBABILITY THEORY THE LOGIC OF SCIENCE Author: E. T. Jaynes

SDMA 阻塞率的仿真实现 主要介绍了FD 和 DL 的阻塞率Erlang源代码

亲测好用，挺不错的资源，大家快来下载吧！挺有用的！需要的话可以来下载哦！网上大部分后面没有答案，这个是很全的 (Solution Manual)Probability and Statistics,4th Edition by Morris H. Degroot

very excellent book for people who just start learning probability theory. it uses plain english, it is easy to understand.

有意思的matlab代码最小概率流学习（MPF） MPF是一种用于非标准化概率模型中参数估计的技术。 该文件中对此进行了描述： J Sohl-Dickstein，P Battaglino，MR德威斯最小概率流学习国际机器学习大会（2011） 该存储库包含为Ising模型和RBM实现MPF的Matlab代码。 目录结构如下： MPF_ising /-Ising模型中的参数估计 MPF_RBM_compare_log_likelihood / -受限玻尔兹曼机器中的参数估计。 该目录还包含将通过伪似然和对比发散训练的小型RBM与通过MPF训练的小型RBM的对数可能性进行比较的代码。 如果您对使用MPF建立神经尖峰数据的Ising模型感兴趣，还应该在查阅Liberty Hamilton的存储库。

Probability and Random Processes with Application to Signal Processing，经典的信号处理教程，英文原版，非扫描版，带部分书签

Feller的权威教材，原先因为不能传大于10M的文件，所以是拆分了上传的，现在作为一个整体传上来。