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求二值图的算法园程序，在指定的目录下输入图像名称，就可以在Matlab的M文件中运行得到图像的二值图，并输入图像对应的矩阵。根据轮廓下可以生成一个二值图，并把它的图像输出。(Figure 2 value seeking algorithms garden program, in the specified directory name of the input image, we can run Matlab M-file to be binary image map and the input image corresponds to the matrix. Contour may be generated according to a binary image, and to its image output.)

saleh valenzeula model at60 Ghz implemented.

该程序包实现的是无味(Unscented)粒子滤波算法，与一般粒子滤波的不同处是：采用UKF近似粒子滤波的建议分布函数。(The package to achieve the tasteless (Unscented) particle filter, particle filter in general the differences are: use of UKF approximate particle filter proposal distribution function.)

Wind energy is one of the fastest growing energy and it will continue to grow around the world

选题二、基于matlab简单图像处理系统用中值滤波方法消除噪声(Two topics, based on matlab image processing system with a simple median filter to eliminate noise)

该算法是粒子群算法和网格直接搜索算法的结合，具有稳定性高的优点。(This is a combination of particle swarm optimization algorithm and grid direct search algorithm.)

图像修复技术的一种技术 PDE算法的matlab简单的实现(The PDE algorithm of image restoration technology is a simple implementation of MATLAB algorithm)

三维电磁场FDTD程序（3D-FDTD matlab）PEC边界(（3D-FDTD matlab）PEC)

MATLAB优化工具箱使用教程，含有具体应用与实例(MATLAB optimization toolbox tutorial, containing specific applications and examples)

为实现合成孔径雷达（SAR）图像分类算法的测试与评估，将VC/Matlab 混合编程技术应用到SAR 图像分类平台开发中，分析与 比较了4 种VC/Matlab 混合编程方法及各自优缺点，并着重研究了基于组件对象模型（COM）的VC/Matlab 混合编程方法。使用Matlab COM 编译器创建了SAR 图像分类算法组件，在VC 中调用其导出的接口函数。在此基础上，完成了SAR 图像分类平台的实例开发且 可脱离Matlab 环境运行。实验结果表明，该方法较好地发挥了VC 与Matlab 各自的优势，提高了SAR 图像分类平台开发的效率。(In order to test synthetic aperture radar （SAR） image classification algorithm，VC/Matlab mixed programming technology was used in SAR image classification platform development. Four VC/Matlab mixed programming methods were introduced and analyzed. Comparing with other three methods，the method based on component object model （COM） was studied particularly. SAR image classification algorithm component was created by Matlab COM complier，and its interface function could be invocated with VC. Using this method，a SAR image classification platform was realized. The platform could run without Matlab. The experimental result shows a good combination of VC and Matlab. So，developing efficiency could be enhanced a lot.)