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本压缩文件为典型网络MATLAB实现程序的源代码(WS.net)

fonction pour calculer angle

this is bpsk code in matlab

经典算法 虽然小，但是经常用到。尤其是有的时候面试(Classical algorithm may be small, but often used. Sometimes the interview, especially)

在matlab开发环境下，实现彩色图片的车牌定位及车牌字符的分割(In matlab development environment, to achieve color picture of the license plate location and license plate character segmentation)

ANFIS网络编程环境下的变量选择程序，通过确定非相关性分析挑选适合确定输出的输入变量(ANFIS network programming environment variable selection procedures, by determining the selection of non-correlation analysis to determine the output of the input variables for)

自己编写的数字接收机程序，多相信道化接收机MATLAB程序，DDC程序(An DDC program by myself)

基于matlab的电力系统谐波抑制研究。对一座110kv变电站进行建模，并对谐波进行分析。介绍了利用无功补偿进行谐波抑制的措施。(Matlab-based Power System Harmonic Suppression. On a 110kv substation modeling, and harmonic analysis. Introduced the use of reactive compensation for harmonic suppression measures.)

％radon transform clear all ％ N=800 n=1:N fs=200 t=n/fs x1=exp(j*2*pi*(5*t+0.5*5*t.^2)) x2=exp(j*2*pi*(5*t+0.5*15*t.^2)) x=x1+x2 ％N=length(x) ％ ambifunb(x ) ％*****************************************RAT naf=ambifunb(x) htl(abs(naf)) ％ [wh,rho,theta]=htl(abs(naf)) colormap([0,0,0]) ％ xlabel( 极半径 ) ％ ylabel( 角度 ) ％**************************************％找出峰值点的坐标,计算初始频率和调频斜率(正确) ％找出峰值点的坐标 b=max(max(wh)) [u,a]=find(wh>=0.8*b) ( Radon transformclear all N = 800 n = 1: N fs = 200 t = n/fs x1 = exp (j* 2* pi* (5* t+ 0.5* 5* t. ^ 2)) x2 = exp ( j* 2* pi* (5* t+ 0.5* 15* t. ^ 2)) x = x1+ x2 N = length (x) ambifunb (x)***************************************** RATnaf = ambifunb (x) htl (abs (naf)) [wh, rho, theta ] = htl (abs (naf)) colormap ([0,0,0]) xlabel (polar radius) ylabel (angle)************************************** to find the coordinates of the peak point, calculating the initial slope of the frequency and FM (right) find the peak point of the coordinates b = max (max ( wh)) [u, a] = find (wh)

这是对广义高斯分布中两个参数alpha,beta的估计方法，对自然图像的大量统计特征就符合这一分布。(function [f, g] = dggbeta(beta, absx) DGGBETA Derivative of generalized Gaussian pdf with respective to beta [F, G] = DGGBETA(BETA, ABSX) Return partial derivative and second order partial derivative This is an utility function for GGMLE ABSX is the distance of the data from the mean Function is undefined for negative beta if beta <= 0 f = NaN g = NaN )