一个好使的双向PCS控制仿真测试源程序

平稳随机信号的参数模型功率谱估计——模型的Burg法求参数(AR-BURG)

PWM PI controller simulink matlab

本人用matlab编写的rels(最小二乘法），rls(递推增广最小二乘法),riv(辅助变量法递推算法)的程序，都是2阶的，稍改动就可以变成其它阶次(I use matlab prepared rels (least squares), rls (augmented recursive least squares method), riv (auxiliary variable method recursive algorithm) procedure, are 2 bands, a little change can be turned into other order)

decodeLogDomain LDPC Alg

对k近邻方法进行改进，knn方法中自动获取k值(Automatic selection of K value in KNN algorithm)

说明：  滑模控制，基于速度环的控制改进算法，滑模控制是变结构控制，又是非线性控制算法，应用于电机领域(Sliding mode control is an improved control algorithm based on speed loop. Sliding mode control is a variable structure control and a non-linear control algorithm, which is applied in the field of motor)

说明：  pid在matlab编程的实际运用,利用simulink编写程序(PID in the actual application of MATLAB programming, using Simulink to write the program)

Bai tap dien dai hoc cong nghe

多用户检测器的性能分析和仿真研究，有详细的源代码，希望各位有用(Multi-user detector performance comparison analysis of simulation studies, the main simulation file has detailed instructions)

最小冗余最大相关性（MRMR）（MRMR.M） 需要外部库。详情请见MRMR。下载一个更新版本的互信息工具箱 偏最小二乘（PLS）回归系数（ReGCOEF.m） 使用MATLAB统计工具箱中的PLSReress ReliefF（分类）和RReliefF（回归）（ReleFracePr.M.） 从Matlab STATS工具箱中包装Releff.m。这是Matlab R2010B以后提供的。 ReliefF的另一个选择是使用ASU特征选择工具箱中的代码。这使用WEKA工具箱的ReleFEF，因此需要额外的库。请参阅相应的文档。 费雪评分（Fisher评分） 围绕ASFS特征选择工具箱围绕FSFisher。M(Minimum Redundancy Maximum Relevance (mRMR) (mRMR.m) Needs external library. See mRMR.m for details. Download a newer version of the mutual information toolbox Partial Least Squares (PLS) regression coefficients (regCoef.m) Uses plsregress.m from MATLAB statistics toolbox ReliefF (classification) and RReliefF (regression) (relieffWrapper.m) Wraps around relieff.m from the MATLAB stats toolbox. This is available MATLAB r2010b onwards. Another option for ReliefF is to use the code from ASU Feature Selection toolbox. This uses ReliefF from weka toolbox and hence needs additional libraries. Please see the corresponding documentation. Fisher Score (fisherScore.m) Wraps around fsFisher.m from the ASU Feature Selection toolbox)