post-phase-correction

跳频通信过程仿真。包括调解，扩频，接扩，解调全过程。(Simulation of frequency hopping communications. Including mediation, spread spectrum, and then expand, the whole process of demodulation.)

argox cp-3140的Visual C#测试用例。(argox cp-3140 Visual C# test example。)

function g=distance_classify(A,b) 距离判别法程序。 输入已分类样本A（元胞数组），输入待分类样本b 输出待分类样本b的类别g 注：一般还应计算回代误差yita 输入已知分类样本的总类别数n 每类作为元胞数组的一列(function g = distance_classify (A, b) from the Criterion procedures. Input samples have been classified A (cell array), the importation of samples for classification b output samples for classification g categories b Note: the calculation should also be back on behalf of the general error input yita of the total known types of classification of the number of samples n each Cellular-type array as a)

绘制正弦曲线和余弦曲线，在MATLAB命令窗口中输入 求方程的全部根(Draw sine curve and cosine curve Root of equation)

it s sort and get an array then it deliver sorted array to user

预处理的源定位 ------------------------------------- 各种脚本用于处理源定位中使用的时间数据。 Time2Frames.m mutilchannel时间数据转换为频谱帧 Time2TF.m 时间数据转换为相对传递函数的帧到通道1。 Frames2R.m 频谱帧转换为（freqeuncy而定）的协方差矩阵。 R2C.m 转换协方差矩阵噪声子空间（用于音乐）。 Clean_Source.m 从协方差矩阵中删除第n个最强的源极（S）。(Preprocessing for source localization ------------------------------------- Various scripts for processing time data to be used in source localization. Time2Frames.m Converts mutilchannel time data to spectral frames Time2TF.m Converts time data to frames of transfer function relative to channel 1. Frames2R.m Converts spectral frames to (freqeuncy dependent) covariance matrices. R2C.m Converts covariance matrices to noise subspace (for MUSIC). Clean_Source.m Removes the nth strongest source(s) from the covariance matrix.)

matlab 牛顿差值 拉格朗日差值 三次样条差值 (matlab newton )

基于SIMULINK，风电仿真所用到的模型，希望有帮助(SIMULINK, wind power simulation model used, it is helpful)

说明：  变分模态分解程序，包括函数和测试程序，已加中文注释，另有说明文档。(The program of variational mode decomposition, including function and test program, has been annotated in Chinese and provided with other documents.)

说明：  做生成数(使用0.1做因子),之后13年的数据按统计方法标准化后输入,训练,仿真,对比结果。这个过程相当于插值计算(Generated to do a few (make use of 0.1 factor), after 13 years of data input after the standardization of statistical methods, training, simulation, comparing the results. This process is equivalent to interpolation calculation)