EKF

现代数字信号处理 ESPRIT算法仿真 (single and system ，matlab ESPRIT)

可对OFDM信道进行预测，对初学者会有帮助~(OFDM Channel estimators.It will be helpful1)

matlab 一维小波分解函数,其功能包括分解与重构 (matlab ?晃 ??????????数, 其 ?| 能 ?? ???庥胫??)

a=load( q.txt ) width=input( 请输入窗宽 ) step=input( 请输入步长 ) m=length(a) for i=1:floor((m-width)/step+1) s(i,1:width)=a(1,1+(i-1)*step:width+(i-1)*step) end b=max(max(s)) M=s./b Rs=input( 请输入本体集半径 ) nd=input( 请输入检测器数模 ) k=1 while k<=nd d{k}=rand(1,width) for i=1:floor((m-width)/step+1) if (norm(d{k}-s(i,:)))^2<Rs break end end k=k+1 end for j=1:nd for i=1:floor((m-width)/step+1) R(i)=(norm(d{j}-s(i,:)))^2(a = load (' q.txt' ) width = input (' Please enter the window width' ) step = input (' Enter step size' ) m = length (a) for i = 1: floor ((m-width)/step+1) s (i, 1: width) = a (1,1+ (i-1)* step: width+ (i-1)* step) end b = max (max (s)) M = s./b Rs = input (' Please enter the body set radius' ) nd = input (' Please enter the number of detector modules' ) k = 1 while k < = nd d {k} = rand (1, width) for i = 1: floor ((m-width)/step+1) if (norm (d {k}-s (i ,:)))^ 2 <Rs break end end k=k+1 end for j=1:nd for i=1:floor((m-width)/step+1) R(i)=(norm(d{j}-s(i,:)))^2)

关于matlab在通信系统的使用的很好讲义，可以了解matlab在通信领域的使用(Good lecture notes on matlab in the use of communication systems, we can understand the use of matlab in the field of communications)

混沌时间序列算法中进行FFT变换程序，求解平均周期及功率谱。(Chaotic time series algorithm the FFT transform procedure for solving the average cycle power spectrum.)

The file introduces a modelling for the photovoltaic array panel.

sor迭代法，是数值分析中很重要的一种，源码为其在matlab中的实现。(sor iterative method, numerical analysis is a very important one in the matlab source code for its realization.)

事先计算图像的标准差，可以用来评判图像变换是否可信(Calculate the standard deviation of the prior image can be used to judge the credibility of image transformation)

本去噪程序包，包含了多种小波阈值去噪算法，包含了小波变换算法的具体实现，去噪算法的具体实现，提供了一个统一的界面，便于初学者学习(this denoise package,includes servel kinds of denoise method that based on threshlod,and it has detail realization of wavelet transform,denoise method,GUI.it is convevient for beginners)