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这是一个关于核模糊聚类算法的例子希望有用(This is a fuzzy clustering algorithm on nuclear examples hope that useful)

说明：  基于MATLAB平台的分形图形的模拟 本文介绍了分形几何中的Sierpinski地毯和Vicsek图形，讨论了MATLAB平台下采用向量化 编程技术绘制Sierpinski地毯和Vicsek图形的问题，并给出了向量化程序和运行结果。(MATLAB-based platform for the simulation of fractal graphics In this paper, fractal geometry of the Sierpinski carpet and Vicsek graphics, discussed under the MATLAB platform programming techniques used to quantify the Sierpinski carpet and Vicsek drawn graphics, and gives the procedure to quantify and operating results.)

本程序是采用维特比算法的软输入软输出的仿真程序(this procedure is used Viterbi Algorithm soft-input soft-output of the simulation program)

A Corner Detector based on Global and Local Curvature Properties，using GUI.(A Corner Detector based on Global and Local Curvature Properties, using GUI.)

camshift算法的简单的matlab源程序，用于视频跟踪(camshift simple algorithm matlab source code for video tracking)

matlab卷积码编译码译码器设计仿真，做毕业论文很有参考价值(matlab convolutional code decoder codec design simulation, doing thesis of great reference value)

matlab编程中，蒙特卡洛抽样的源程序，蒙特卡洛算法应用(Matlab programming, Monte Carlo sampling of the source, the Monte Carlo algorithm is applied)

空间谱估计 经典music算法 2个例子(DOA MUSIC)

to retrive signal in matrix form from strucutre which obtained from scope of simulink

he files in this package comprise the Matlab implementation of a foreground segmentation algorithm based upon graph cuts, described in: Better Foreground Segmentation Through Graph Cuts, N. Howe & A. Deschamps. Tech report, http://arxiv.org/abs/cs.CV/0401017. The file extractForeground.m contains a sample function that will perform a complete foreground segmentation for static camera video. It uses a number of parameters, which are described in the documentation. An attempt was made to choose sensible default values, but they may need to be adjusted for some videos. More generally, the implementation in extractForeground.m is only a suggestion of how the graph-based segmentation might be used. The same approach can be applied with other (perhaps time-adaptive) background models. The key step is at line 113 of the code, once the deviation array has been created. The graph-cut segmentation can be applied similarly to a deviation matrix computed in any other way.