一个C#写的FFT函数，希望能给大家以提示。没有压缩密码。

//=== === === === === === === = //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

糊涂先生给他的五个朋友写信，他写了五封信，但是当他的朋友收到信后，都告诉他：“你的信寄错了”。那么请你计算一下：出现这种情况的概率有多少？（假设糊涂先生是随机地往信封里装信的），你能不能把所有的情况都列出来呢-Mr. foolish to write him five friends, he wrote five letters, but when his friend received a letter, told him:

经典关联分析算法apriori java版。可解决关联分析问题，比如分析超市购物关联关系，产品交叉销售可能性，客户价值提升等

Description:  This application functions as a packet error rate (PER) tester.  One node is set up as transmitter and the other as receiver. The role and  configuration parameters for the PER test of the node is chosen on initalisation  by navigating the joystick and confirm the choices with S1.  The configuration parameters are channel, burst size and tx power. Push S1 to  enter the menu. Then the configuration parameters are set by pressing  joystick to right or left (increase/decrease value) and confirm with S1.

目标追踪算法，自己结合 mean shift + kalman filter，效果还不错，半自动跟踪。毕设要求，结合了最简单的mean shift 算法，以及一个二维卡曼滤波器，实现了目标的实时跟踪监测，效果已经达到要求，在这里分享给大家。

资源描述通过对20所高校的科研能力进行了调研和评价，选取其中较为重要的11个评价指标的数据，并结合离散Hopfield神经网络的联想记忆能力，建立离散Hopfield高校科研能力评价模型，并对其进行仿真测试。

本实验主要涉及解线性方程组的列主元消去法.通过编辑程序,能更深入地了解到列主元消去法的内涵.并且通过计算比较,也可以了解到数据的精度及舍入误差等一系列有关因素.-this study involved solving linear equations of main-element elimination. Through the editorial process, to better understand out to the main yuan elimination connotations. through calculation and comparison, Data can also understand that the accuracy of rounding error and a series of other relevant factors.

matlab 例程-Matlab routines

三次样条插值函数的构造

一个用分行来画树的程序，vb写的-using a tree branch to paint the procedures written in vb