PKU_Summer

说明：  统计学习是计算机及其应用领域的一门重要的学科本书全面系统地介绍了统计学习的主要方法，特别是监督学习方法，包括感知机、K近邻法、朴素贝叶斯法、决策树、逻辑斯谛回归、与最大熵模型、支持向量机、提升方法、EM算法、隐马尔可夫模型和条件随机场等。(Statistical learning is an important subject in the field of computer and application of this book comprehensively systematically introduces the main methods of statistical learning, especially the supervision method of study, including the perception, K neighbor method, naive bayesian method, decision tree, logistic regression, and the maximum entropy model, support vector machine (SVM), promotion methods, the EM algorithm, the hidden markov model and conditional random field, etc.)

说明：  预加重与去加重介绍；对高速信号进行补偿；(Introduction of Pre-emphasis and De-emphasis)

In many areas of commerce, government, academia, and hospitals, large collections of digital images are being created. Many of these collections are the product of digitizing existing collections of analogue photographs, diagrams, drawings, paintings, and prints. Usually, the only way of searching these collections was by keyword indexing, or simply by browsing. Digital images databases however, open the way to content-based searching. In this paper we survey some technical aspects of current content-based image retrieval systems.

说明：  结构随机振动，很经典的英文原版课本。Random Vibrations Analysis of Structural and Mechanical Systems(Random Vibrations Analysis of Structural and Mechanical Systems)

基于Verilog的FPGA设计时序分析约束详细解释与使用方法(FPGA timing constraints)

说明：  关于粒子滤波的原理及介绍，有相关MATLAB代码(About the principle and introduction of particle filtering, there are related MATLAB code)

板波资料和书，里面有瑞利波和lamb波的相关资料(Plate wave data and books)

《推荐系统实践》作者：项亮； 书籍全部章节配套源代码； 仅供学习分享，如有侵权立刻删除。(Author of Recommendation System Practice: Xiang Liang; All chapters of the book are accompanied by source code. For learning and sharing only. If there is any infringement, delete it immediately.)

支持向量机入门教材。这种方法现在在模式识别十分火。解决高维，少样本的训练问题(Introductory teaching matrial of SVM, which draws many interests of scholars in the field of pattern recognition. It is good at solving the problem of high dimentional,few samples )

ibm AIX 资料，很详细，个人觉得很有用。(ibm AIX Data, very detailed, personal feel useful.)