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Matlab语言编写的2维粒子群算法进行函数最优化的源代码，并附有AVI视频演示！(2-D particle swarm optimization source code for optimization (with the AVI video!))

基于Matlab的多孔算法提取图像边缘,可以更好地提取图像边缘(Edge extraction porous algorithm based on Matlab)

clossed loop boost converter mpdel

The aim of this paper is to describe a novel and completely automated technique for carotid artery (CA) recognition, far (distal) wall segmentation, and intima–media thickness (IMT) measurement, which is a strong clinical tool for risk assessment for cardiovascular diseases. The architecture of completely automated multiresolution edge snapper (CAMES) consists of the following two stages: 1) automated CA recognition based on a combination of scale–space and statistical classification in a multiresolution framework and 2) automated segmentation of lumen–intima

很好用的matlab源代码，值得作为参考。源代码可以直接拿来应用。(can run smooth)

FMCW MATLAB R2014B实现(Automotive Adaptive Cruise Control Using FMCW Technology)

用训练数据优化DPCM方法，对一个余弦信号数据进行标量量化。(we take optimize the training data DPCM method for the cosine signal data scalar quantization to get a wonderfull understanding.)

包含了目前常用的各种重采样算法的matlab代码，可直接在滤波算法中调用，不用修改。(Contains a variety of currently used resampling algorithm matlab code, can be directly in the filtering algorithm in the call, need not be amended.)

This is a simulink model for single phase half bridge pwm inverter

做过模糊PID的朋友很多遇到过这种问题，就是仿真启动不起来，停留在e-7等地方或者仿真很慢，自次上次有个朋友说改变步长能解决这个问题，最后的曲线能达到满足要求的时候，我让他找个例子他就没有后文，以前我做了很多这样的模糊PID，但靠改变步长并没有解决问题，仿真曲线直接发散出去了，我自己这两天也总在思考这个问题，通过不断的调试总结，明白了不少，给遇到这个问题的朋友讲解一下解决办法吧，以一个例子详解：(Done a lot of friends of the fuzzy PID encountered this problem, simulation start up, stay in the e-7 and other local or simulation is very slow, have a friend who said to change the step size to solve this problem since the times the last, the finalcurve to achieve to meet the requirements when I asked him to find examples of his later, I have done a lot of fuzzy PID, but by changing the step does not solve the problem, the simulation curve directly divergence out, Itwo days always thinking about this problem, summarized by the debug and understand a lot of friends to experience this problem to explain the solution, an example Detailed:)