Project1

2011年最新维纳滤波器的设计，课程设计验收结果为优(In 2011, the latest wiener filter design, course design acceptance for optimal results)

The aim of this application is to implement scalable mpeg type compression by varying DCT coefficients and finding minimum number of DCT coefficients that can give minimum acceptable quality.. This application only works for gray scale.

stats 用于检验回归模型的统计量，有三个数值：相关系数r2、F值、与F对应的概率p.相关系数r2越接近1，说明回归方程越显著；F > F1-α（k，n-k-1）时拒绝H0，F越大，说明回归方程越显著；与F对应的概率p 时拒绝H0，回归模型成立.(stats for the test statistic of the regression model, there are three values: the correlation coefficient r2, F value, and F corresponds to the probability p. The correlation coefficient r2 more close to 1, note the more significant regression equation F> F1-α (k, nk-1) refused to H0, F the bigger shows the more significant regression equation F corresponds with the probability p refused H0, set up a regression model.)

一个RLS的算法程序，应该对大家有帮助的。(?桓 鯮LS的算 ??绦????| ????#39 ??矣??镏???)

基于Arnold变换的matlab实现 各种置乱算法简介(Matlab implementation based on Arnold transform us all scrambling algorithm)

精通MATLAB计算科学书源代码，原书正版CD第三张源代码(Proficient in computer science book MATLAB source code, the third original CD to the book source code)

该程序可以求取电力系统低频振荡特征根，输入数据为三机9节点系统(The program can strike a power system low frequency oscillation characteristic roots, the input data for the three-machine 9-bus system)

matlab中用于进行fourier变换的GUI程序(matlab in fourier transform used for GUI program)

LS盲信道估计的代码程序 matble环境下运行(LS-blind channel estimation procedure code matble environment running)

设r是f(x) = 0的根，选取x0作为r初始近似值，过点（x0,f(x0)）做曲线y = f(x)的切线L，L的方程为y = f(x0)+f (x0)(x-x0)，求出L与x轴交点的横坐标 x1 = x0-f(x0)/f (x0)，称x1为r的一次近似值。过点（x1,f(x1)）做曲线y = f(x)的切线，并求该切线与x轴交点的横坐标 x2 = x1-f(x1)/f (x1)，称x2为r的二次近似值。重复以上过程，得r的近似值序列，其中x(n+1)=x(n)－f(x(n))/f (x(n))，称为r的n+1次近似值(Let r is f (x) = 0 root, select the initial approximation x0 as the r, over point (x0, f (x0)) to do the curve y = f (x) the tangent L, L the equation y = f ( x0)+ f ' (x0) (x-x0), find the intersection of L and the x-axis of abscissa x1 = x0-f (x0)/f' (x0), x1 is called an approximation r. Through points (x1, f (x1)) to do the curve y = f (x) the tangent, and find the intersection of the tangent with the x-axis of abscissa x2 = x1-f (x1)/f ' (x1), x2 is called r the second approximation. Repeat the process, get an approximation of the sequence r, where x (n+1) = x (n)-f (x (n))/f ' (x (n)), as an approximation of r n+1 times)