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多元统计分析中的因子分析的代码，比较简洁(code of factor analysis in multiple statistics analysis)

run in matlab 6.0 or above UWB channel simulink .(run in Matlab 6.0 or above UWB channel simul ink.)

matlab写的将fig格式图片转成jpg格式的源代码(matlab write the fig format jpg format image into the source code)

说明：  单纯形法matlab程序，输入A,b,c，得到整个过程的单纯形表与最优解，最优值，每一步变换的单纯形表都有给出，完全没有错，很详细，有运行结果说明。(The simplex method matlab program, input A, B, C, get the simplex table and the optimal solution of the whole process, the optimal value, the simplex table of each step transformation are given, there is no error at all, very detailed, there are running results.)

自动提取目标图像轮廓边缘，同时分辨其颜色。(Automatic edge contour extraction target image, at the same time to tell its color.)

四种聚类算法源代码及示例代码,本程序的最终目的是形成一套标准的用于聚类、可扩展的工具。包括的内容有1. 聚类算法：Kmeans和Kmedoid算法、FCMclust, GKclust, GGclust算法 2. 评估分类原型：程序可以在二维图像上绘制出聚类的结果 3. 验证：程序给每一个算法提供验证机制，每个聚类算法会统计Partition Coefficient (PC), Classification Entropy (CE), Partition Index (SC), Separation Index (S), Xie and Beni s Index (XB), Dunn s Index (DI) and Alternative Dunn Index (DII)几种衡量指标。(Four kinds of clustering algorithms source code and sample code, the ultimate goal of this program is to form a set of standards for clustering, scalable tools. Including the contents of a. Clustering algorithm: Kmeans and Kmedoid algorithms, FCMclust, GKclust, GGclust algorithm 2. Assessment classified prototypes: programs can be plotted in two-dimensional image, the results of clustering 3. Verify: Program to provide an algorithm to each authentication mechanism, each clustering algorithm will calculate Partition Coefficient (PC), Classification Entropy (CE), Partition Index (SC), Separation Index (S), Xie and Beni' s Index (XB), Dunn' s Index (DI) and Alternative Dunn Index (DII) of several metrics.)

基于c#的互相关函数计算，基于c#的互相关函数计算，基于c#的互相关函数计算，(Cross Correlation)

这是TD算法的逆过程，首先将时间序列，划分为相邻点的短序列，当然此时的拟合误差为0，因为第一点和第二点的连线，原始点都落在线段上。将相邻两个线段连接起来，此时每条线段包含三个原始点，计算中间那个点的拟合误差。这样，所有这些三个点的线段中的中间点的拟合误差计算出来后，找出误差最小且误差小于阀值R的分段，作为第一条包含三个点的线段。 在上面的基础上，第一条分段同样的和相邻线段连接，然后计算每一条分段的拟合误差，再找出误差最小且小于阀值R的分段，作为第二个分段。依次方式循环，直到所有分段的拟合误差都小于阀值R，分段结束。 (This is the reverse process of TD algorithm, the first time series is divided into short sequences adjacent dots, of course fitting error is zero at this time, because the first and second points of connection, the original point fall line on. The two adjacent segments are connected, then each segment contains three original point, the intermediate fitting error calculated that point. Thus, after all these segments fitting error of three points in the intermediate point calculated to find the minimum error and the error is less than the threshold R segment, as the first line contains three points. Based on the above, the first segment and the adjacent line segment connecting the same, and then calculate a fitting error for each segment, and then find the smallest error and less than the threshold R segment, as the second segment . Followed by a cyclic manner until all segments fitting error is less than the threshold R, segment ends.)

统计直方图 matlab 概率密度函数和统计直方图的拟合(Histogram matlab probability density function and a histogram fitting)

说明：  使用高斯混合模型（Gaussian Mixture Model）拟合风电场中预测误差分布(Using Gaussian mixture model to fit prediction error distribution in wind farm)