QPSK发射机&接收机

windows驱动开发资料，深入驱动核心，剖析操作系统底层运行机制。(Windows driver development data, in-depth driving the core, analyzing the underlying operation mechanism of the operating system.)

说明：  2020年数学建模国赛A题回焊炉控温，使用粒子群算法，差分法，牛顿冷却公式，绘制炉温曲线，其中粒子群算法进行了优化处理(In 2020 mathematical modeling, the temperature control of reflow furnace in question a of national competition of mathematics is used. The temperature curve is drawn by using particle swarm optimization algorithm, difference method and Newton cooling formula, in which the particle swarm optimization algorithm is optimized)

说明：  求解兰伯特问题的matlab代码，非常好用(The matlab code for solving Lambert problem is very useful.)

使初学者能够很容易明白TCL这种脚本语言的一些基本知识，很快掌握它的编写。(So that beginners can easily understand the TCL scripting language that some basic knowledge, and soon mastered it is written.)

MATLAB基础视频教程是关于matlab入门的菜鸟教程(MATLAB basic video tutorial)

使用QT实现扫雷，包括中键等功能。界面风格与windows扫雷类似(To use QT achieve demining, including the key functions)

支持向量机（svm）的学习资料和响应的代码学习。(Support vector machine (svm) learning data and some code learning.)

Ni－LabVIEW的源程序的第三个，具体请看内容 很少见的哦-Ni-LabVIEW source of the third, the specific content rarely see Look at the Oh! !

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...)

说明：  mnist数据导入用于深度学习人工智能机器学习(Mnist data import for deep learning artificial intelligence machine learning)