The-sorting-process

a routine for Gaussian elimination together w/ gepivot.m which you will need for running

本例演示：如何依靠图形窗的 UserData 属性传送用户控件的图柄，从而保证回调动作正确执行。(the cases demonstrate : how to rely on the graphics window UserData attributes transmission users control plans handles, callback action so as to ensure correct implementation.)

queues and stacks implementation

基于RSSI的测距定位算法，可以直接自己写demo然后进行测试，十分的方便(RSSI-based distance positioning algorithm can write your own demo and then test, very convenient)

小波去噪matlab仿真算法，用于ECG心电信号去噪(wavelet filter Matlab)

正交最小二乘辨识算法 该算法除了实现最小二乘辨识功能之外而且能按照各项重要性将其逐一选出并且估计相应系数(OLS Orthogonal Least Quares. [x, ind] = OLS(A,b,r) gives the solution to the least squares problem using only the best r regressors chosen from the ones present in matrix A. This function also returns in the vector ind the indexes of the best r regressors (i.e., the best columns of A to use). If r is equal to n, the solution x given by OLS is the same as the solution given by A, but in ind we still have the regressors sorted by their importance. This means that one can perform a feature selection by taking the first k entries in ind (k<r).)

基于FDTD的1D点源分布远远场场分布，程序简单，易于阅读和使用，适合初学者。 (FDTD-based one-dimensional distribution of far field point source field distribution, the program is simple, easy to read and use, suitable for beginners.)

高速铁路路基沉降是一个复杂的系统过程,涉及不同时期、不同工况,选用单一的预测模型不足以反映路基整体的变形规律.Logistic模型及Verhulst模型的曲线均为S形,可以反映全过程的地基沉降与时间的关系.针对路基填筑期和降水期两个时段利用MATLAB软件编制程序计算模型参数,得到Logistic模型和灰色Verhulst模型,进而求得两者的最优加权组合模型.对比结果表明:在路基填筑期由两者的最优加权组合模型预测得到的结果与实测结果较吻合,拟合精度高于单一模型 而在降水期Verhulst模型的预测值更接近实测值,平均相对误差约为1.75％,拟合精度较高.(High-speed railway subgrade settlement process is a complex system involving different times and in different conditions, the choice of a single forecasting model does not adequately reflect the overall deformation of roadbed. Curve Logistic model and Verhulst models are S-shaped, the whole process can be reflected foundation settlement versus time. against roadbed construction period of two hours and precipitation using MATLAB software programming model parameters, the Logistic model and gray Verhulst model, and then get the optimal model of a weighted combination of the two. comparative results indicate : results and experimental results in the roadbed construction period by the weighted combination of the best of both models predicted than the anastomosis fitting accuracy than a single model precipitation predicted value of Verhulst model closer to the actual value of the average relative error approximately 1.75 fitting accuracy.)

用matlab实现投资问题（类似于0-1背包问题，但更复杂）的动态规划(Problem with matlab realized investment (like the 0-1 knapsack problem, but more complex) dynamic programming)

Python for Kids, Snake Wrangling for Kids - Learning to Program with Python 3, Windows ed. (2007)