lowercase amount to the amount of capital used in capital letters and lowercase...

三态树：一个树控件的派生控件，完成item的三种状态-Tri-state tree: A tree control derivative controls, the three states to complete item

以优化SVM算法的参数c和g为例，对GSA（引力搜索算法）MATLAB源码进行了详细中文注解。是很好的学习材料。

地震模拟资料数字化的过程中，会存在数据打折、台阶等现象，该程序用于把数字化后的数据去打折、去台阶-Earthquake simulation data digitization process, there will be discounts of data, step of such a phenomenon, the program for the digital data to a discount, go to step

Bisection Method - Numerical ananlysis-Bisection Method- Numerical ananlysis

//=== === === === === === === = //函数说明 //函数名称：PolyFit //函数功能：最小二乘法曲线拟合 //使用方法：double *x ---- 存放n个数据点的X坐标 // double *y ---- 存放n个数据点的Y坐标 // int n -------- 给定数据点个数 // double *a ---- 返回m-1次拟合多项式的m个系数 // int m -------- 拟合多项式的项数，即拟合多项式的最高次为m-1。要求m20，则本函数自动按m=min{n,20}处理 // double *dt --- dt[0]返回拟合多项式与各数据点误差的平方和；dt[1]返回拟合多 // 项式与各数据点的误差绝对值之和；dt[2]返回拟合多项式与各数据 // 点误差绝对值的最大值 //注意事项：拟合多项式的形式为 y = b0 + b1*(x-Xavr)... -//=== === === === === ==== === === === === === === ==== === =// function annotations// function name : PolyFit// Function functions : Least Squares Curve Fitting// Use : double* x n-store data point coordinates of the X//* y double-storage n data point Y coordinates// int n-------- given the number of data points//* a double---- returned to the m-1 m fit polynomial coefficients// int m-------- polynomial fitting items , which is the highest polynomial fitting time for m-1. Request m

基于DFT的频谱细化程序

对椭圆加密算法中的涉及的求模，求逆以及所有相关点集的计算，并对多倍点的计算做了计算

数据挖掘分类算法决策树学习算法介绍以及SEE5的使用说明-data mining algorithms decision tree classification algorithm presentations and the use SEE5

最小二乘法一般是用来拟合直线和一些线性数据的，就是用一条直线来尽可能的表达若干的点的趋势，当然直线穿过所有的点是最好的，但往往有误差存在，所以拟合出的直线要求误差最小.设这些点为(x1,y1),(x2,y2)....(xn,yn).拟合直线为y=kx+b.-Ordinary least squares method is used to fit a straight line and a number of linear data, that is, as far as possible with a straight line to the point of the expression of a number of trends, of course, a straight line through all the points is the best, but often there is a margin of error, Therefore, a straight line fitting the requirements of the smallest error. established for these points (x1, y1), (x2, y2 )....( xn, yn). fitting straight line y = kx+ b.

蛙跳差分方法，精华分(ˇˍ ˇ） 想～ 蛙跳差分方法，精华分(ˇˍ ˇ） 想～-leap forg