Trnsys17Mannul01

雷达信号理论(林茂庸著） (Radar signal processing by Maoyong Lin)

说明：  This classroom-tested and easy-to-understand textbook/reference describes the state of the art in 3D reconstruction from multiple images, taking into consideration all aspects of programming and implementation. Unlike other computer vision textbooks, this guide takes a unique approach in which the initial focus is on practical application and the procedures necessary to actually build a computer vision system.

说明：  一本介绍ArcObject组件开发的书，介绍GIS二次开发(Copies of the book ArcObject component development, secondary development of GIS introduction)

OReilly电子书Classic Shell Scripting(OReilly book Classic Shell Scripting)

说明：  C++编程指南电子版 ，林锐博士的多年C++编程经验总结，其中C++编程中需要注意的问题和编程技巧总结的不错 (C++ programming guidelines electronically, Dr. Lin Rui years of Experience in C++ programming, including C++ programming problems that need attention and good programming skills summary)

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)

数字信号处理（丁玉美）西电出版社，全书，及课后习题详解(Digital signal processing (Ding U.S.) Western Electric Press, the book, and after-school Exercise Xiangjie)

一种二相码信号多普勒补偿方法的研究与实现，并实现一种基于数字动目标检测 (DM TD)的二相码信号多普勒补偿方法(A two-phase code signal Doppler compensation method of research and realize, and realize a moving target detection based on digital (DM TD) of the two-phase code signal Doppler compensation method)

说明：  这是一本关于python编程的指导用书，非常全面(This is a very comprehensive guide book on Python programming.)

关于关联向量机应用的最新文献！ 提出了一种核主元分析(KPCA)和关联向量机(RVM)相结合的组合建模方法。KPCA-RVM采用KPCA对原始自变量进行非线性变换并提取主成分,形成特征自变量 采用RVM,对KPCA变换后的样本数据进行回归建模,并根据模型的预报能力自适应的确定参与回归的最佳特征变量个数,消除冗余信息干扰,获得强非线性表达能力且预报性能良好的模型。并将KPCA-RVM应用于PTA装置对羧基苯甲醛(4-CBA)含量的软测量建模,结果表明该方法预测精度高于PCA-RVM和RVM。(A novel modeling method integrated KPCA with RVM was proposed. The kernel primary component analysis (KPCA) was employed to identify the principal components from the nonlinear transform data of independent variables, which were regarded as character variables. Regression between character variables and dependent variables was done based on RVM, and the optimal number of the character variables was adaptively determined according to the generalization performance of the regression model. Thus, KPCA-RVM meth...)