DSDP5.8WIN

车间布局优化模型是一个含有较为复杂约束的非线性连续优化模型，可以使用遗传算法进行优化。(Workshop layout optimization model containing is a complicated nonlinear optimization model in a row, you can use the genetic algorithm optimization. )

说明：  采用通用动态尾流理论进行风力机气动力学的计算分析,并用 MATLAB/Simulink进行编 程,建立了风力机传动链的数学模型。 在 MATLAB/Simulink中进行传动链系统的编程运算,建立了 风力机 ADAMS柔性多体结构动力学仿真模型,并利用 MATLAB/Simulink和 ADAMS进行风力机振 动性能的联合仿真。 仿真时将气动载荷加载到风力机叶片结构上,将传动系统模型的反扭矩加到 AD AMS风轮模型上,同时考虑风力机的结构变形对气动性能、传动性能产生的影响。 仿真最终实现了风 力机系统振动性能耦合分析,其数据同实验测试数据比较表明,该联合仿真方法可以较好地模拟风力机 的振动特性。(TheaerodynamicscharacteristicsofwindturbinewerecalculatedbyapplyingGDWthe oryandwereprogrammedin MATLAB/Simulink. Thedrivechainwascalculatedbyapplyingstate spacemethodandalsoprogrammedinMATLAB/Simulink. Themodelofthewindturbinewasbuilt inAdams. Thesimulationofvibrationcharacteristicswascarriedoutsothattheaerodynamicloads andthetorquewereappliedtothestructureoftherotor. Simultaneouslythedeformationofthestruc turealsoaffectedtheloads. Theresultsshowthatthemethodhasexcellentabilitytosimulatethevi brationcharacteristicsalmostthesameastestmeasured.)

matlab编写的实现surf的平台 老外的东西，可以进行验证(matlab prepared foreigner platform surf achieve things, you can verify)

建立了基于matlab的整流器仿真模型，系统运行正常，可在此基础上进行模糊的仿真(Rectifier is established based on matlab simulation model, the system runs properly, this can be simulated on the basis of vague)

自己编的MIMO瑞利衰落子程序，四径，车速20，参数可以修改(Rayleigh fading MIMO compiled its own subroutines, four tracks, speed 20, the parameter can be modified)

edge detection sobel

此程序实现了一种改进的ofdm下的信道估计方法，综合了以往的几种内插方法，并加以改进(This program realise a new channel estimation beneath the ofdm system combining several former intersecting method.Furthermore, certain ameliorations are also being done.)

基于回归理论分析的支持向量代码及m代码顶顶顶顶顶顶(Based on support vector regression analysis code and m code)

多目标粒子群算法优化分布式发电选址 实现了最优目标(Mutil-Objective particle swarm optimization)

全变差求解病态线性方程组的算法说明及其Matlab上的实现代码，在反演问题中常常会用到，全变差正则化具有边界识别强的特点，在图像去噪和恢复方面很有价值！(Total Variation solving ill-conditioned linear equations Matlab algorithm description and implementation code on the inverse problem will often be used, total variation regularization with boundary recognition and strong features, in terms of image denoising and restoration is very value!)