DRFM1

基于帐篷定理的计算矩形巷道中接受点功率大小的仿真(Theorem based on the calculation of rectangular tunnel tent to accept the size of the simulation point of power)

直接转矩控制源码，在simulink的环境下搭建的，绝对有效。可以直观的看到直接转矩控制的运行原理。(DTC control.)

基于互相关matlAB图像配准代码，压缩文件包括源文件，GUI设计文件。程序能自动配准图像，能手动选择要配准的图像(Based on cross-correlation matlAB image registration code, source files, including compressed files, GUI design files. Automatic image registration procedures, registration can manually select the image you want to)

Here, an implementation of Fast Decoupled Load flow is matlab platform is done. This is used for Load flow studies (Electrical).

Monte Carlo Path Integral for Harmonic and Anharmonic Potential(Monte Carlo Path Integral for Harmonic and Anharmonic Potential)

SMART Jammer Project Introduction

说明：  一束5W 的线偏振光以Φ = 45 度方位角振动，垂直入射到玻璃 - 空气表面，该光束波长0.6μm，玻璃介质折射率1.54 @0.6m，当入射角θ从0-70 度变化时，通过给定条件，分别完成如下要求： 画出该光束反射光的光强曲线（I-θ）； 分析该反射光束的偏振态变化，画出偏振方向变化曲线（φ-θ）和偏振光束相位变化曲线 （Φ-θ）。 （注：光束从光密到光疏的界面，在入射角θ 从0-70 度变化中，包括了临界角θc）(Bunch of linearly polarized light 5W to Φ = 45 degrees azimuth vibration, normal incidence to the glass- air surface, the beam wavelength 0.6μm, glass refractive index 1.54 @ 0.6m, when the incident angle θ changes from 0-70 degrees By the given conditions, namely the completion of the following requirements: Draw the reflected light beam intensity curve (I-θ) analysis of changes in the polarization state of the reflected beam, draw the polarization direction of the curve (φ-θ) and polarized beam phase curve (Φ-θ). (Note: the light beam from the optical density of the interface is sparse, the incident angle θ  variation from 0-70, including the critical angle θc))

说明：  这是一个在MATLAB环境下的支持向量机的源代码，是大家学习SVM很好的例子(This is an environment in MATLAB support vector machine source code, is a good example of people learning SVM)

说明：  珍藏版，可实现，新K均值聚类算法，分为如下几个步骤： 一、初始化聚类中心 1、根据具体问题，凭经验从样本集中选出C个比较合适的样本作为初始聚类中心。 2、用前C个样本作为初始聚类中心。 3、将全部样本随机地分成C类，计算每类的样本均值，将样本均值作为初始聚类中心。 二、初始聚类 1、按就近原则将样本归入各聚类中心所代表的类中。 2、取一样本，将其归入与其最近的聚类中心的那一类中，重新计算样本均值，更新聚类中心。然后取下一样本，重复操作，直至所有样本归入相应类中。 三、判断聚类是否合理 采用误差平方和准则函数判断聚类是否合理，不合理则修改分类。循环进行判断、修改直至达到算法终止条件。(NewK-means clustering algorithm ，Divided into the following several steps: A, initialize clustering center 1, according to the specific problems, from samples with experience selected C a more appropriate focus the sample as the initial clustering center. 2, with former C a sample as the initial clustering center. 3, will all samples randomly divided into C, calculate the sample mean, each the sample mean as the initial clustering center. Second, initial clustering 1, according to the sample into the nearest principle clustering center represents the class. 2, as this, take the its recent as clustering center of that category, recount the sample mean, update clustering center. And then taking off, as this, repeated operation until all samples into the corresponding class. Three, judge clustering is reasonable Adopt error squares principles function cluster analysis.after clustering whether reasonable, no reasonable criterion revisio)

能实现人脸的简单匹配算法，本人亲自测试，还行吧(To achieve a simple matching algorithm, face, OK.)