相空间重构

说明：  基于matlab做栅格数据的MK趋势分析(MK trend analysis of grid data based on MATLAB)

说明：  对中国气象网的气象地面日值数据进行合并标准化处理，可以提取指定站点的气象信息，实测好用(By combining and standardizing the meteorological daily data of China Meteorological Network, the meteorological information of designated stations can be extracted, which is easy to use)

说明：  混合藤Copula工具箱 A. Onken and S. Panzeri (2016). Mixed vine copulas as joint models of spike counts and local field potentials. In D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon and R. Garnett, editors, Advances in Neural Information Processing Systems 29 (NIPS 2016), pages 1325-333.(Mixed-Vine Copula Toolbox A. Onken and S. Panzeri (2016). Mixed vine copulas as joint models of spike counts and local field potentials. In D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon and R. Garnett, editors, Advances in Neural Information Processing Systems 29 (NIPS 2016), pages 1325-333.)

（1）实时抓取网络数据。（2）网络协议分析与显示。（3）将网络数据包聚合成数据流，以源IP、目的IP、源端口、目的端口及协议等五元组的形式存储。（4）计算并显示固定时间间隔内网络连接（双向流）的统计量（如上行与下行的数据包数目，上行与下行的数据

说明：  灰色预测模型GM（1，N），可以多因素分析，可对未来数据进行预测。 程序可直接运行，可以更换数据。 预测未来数据时，只需修改T值，以及因变量数据；否则T=0即可。 例如，预测未来2个数据，T=2. 输入数据：因变量x1为400.因变量x2为50；因变量x1为450.因变量x2为90。(The grey prediction model GM (1, n) can analyze many factors and predict the future data. The program can run directly and change data. When predicting future data, only the T value and dependent variable data need to be modified; otherwise, t = 0. For example, predict 2 data in the future, t = 2 Input data: the dependent variable X1 is 400, the dependent variable X2 is 50, the dependent variable X1 is 450, and the dependent variable X2 is 90.)

说明：  此代码可计算Diebold&Yilmaz 溢出指数(The Diebold-Yilmaz Spillover index can be calculated by this code.)

该程序完成了光电编码器的功能，有波形设计，四细分，正传加一，反转减一，有输入输出波形

说明：  method1_glp.m是好格子点法构造均匀设计，method2_pglp.m是方幂好格子点法构造均匀设计，适用于试验点较多的情况(good lattice points method to construct uniform design)

说明：  python程序计算皮尔逊相关系数、最大信息系数以及灰色关联度(Pearson correlation coefficient, maximum information coefficient and grey correlation degree were calculated by Python program)

说明：  实现tSNE降维，已经封装完成，可以直接在matlab使用(Reducing dimension of tsne)