Z源逆变器开路三相SVPWM调制

说明：  基于块分割的图像拼接，将图像按块拼接，缺点是速度很慢，算法有待改善(Block-based segmentation of the image mosaic, mosaic images by block, the disadvantage is very slow, the algorithm needs to be improved)

基于非局部图像去噪模型的遥感图像融合的变分方法。该变分方法采用梯度下降法。(Variational method of remote sensing images nonlocal image denoising model fusion. The variational method using gradient descent.)

以标准化fcm分割为基础的，结合空间隶属度约束的改进算法(Fcm divided based on a standardized, combined with space constraints improved algorithm membership)

说明：  face recognition example for learning

给出了偏微分方程的径向基函数配点法的数值解法，进行了数值模拟，并且给出了图形(The numerical solution of the radial basis function with partial differential equation method, numerical simulation, and gives the graphic )

利用滑模变控制去实现风机的最大功率跟踪。基本原理是控制tip-speed ratio(The use of Sliding Mode Variable fan control to achieve maximum power tracking. The basic principle is to control the tip-speed ratio)

实现bmp位图的图像放大缩小，包含整个mfc的源码文件。(Achieve bmp bitmap image zoom, contains the entire mfc source files.)

CT反投影重建的R-L滤波函数与S-L函数，应用对象为matlab自带shepp-logan模型图像(R-L function and S-L function applying to CT backproject reconstruction)

本算法在Matlab2008b 环境下实现。包括main,san 和ssd 三个函数。 这次实现的算法并不是比较两个已经知道的点是否匹配，而是已知一个图形中的特征点，在另外一个图像中找到与其最匹配的点，匹配度用SAD 或者SSD 来度量。 main.m 是程序的入口，包括生成和读入实验数据，调用sad 函数和ssd 函数求匹配点，最后绘 制出最后的结果。sad.m 是用sad 度量方法在另一图中求解匹配点的函数实现，有3 个参数 y=sad(x,image1,image2)。其中x 是代匹配的数据，image1 是图像1 数据，image2 是图像2 数据。 从理论上分析，ssd 比sad 算法要复杂一点，经过测试，在一幅640*480 的图像中寻找10 个匹配点数据SAD 用时25.062519 秒，SSD 用时25.291432 秒。(The algorithm Matlab2008b environment to achieve. Including the main, san, and ssd three functions. The implementation of the algorithm is not the point of comparing two matches already know, but the known feature points in a graphic, an image found in the other match with the most points, matching measured with the SAD or SSD. main.m is the entry, including the generation and reading test data, call the sad ssd function evaluation functions and matching points, and finally draw the final result. sad.m measure is sad figure in another match point in the function implementation to solve, there are three parameters y = sad (x, image1, image2). Where x is the generation of matching data, image1 is the data image 1, image2 is the image 2 data. From the theoretical analysis, ssd little more complicated than the sad algorithm, tested in a 640* 480 images of 10 match points in the search for data using time 25.062519 seconds SAD, SSD with time 25.291432 seconds. )

2维相控阵方向图，用的是fft算法，验证正确为。(wo-dimensional phased-array pattern, using the fft algorithm, the right to verify.)