ImageSOMQuantization

此函数为matlab函数，可以用来绘制出任意函数的包迹线。(Finds the envelope of an arbitrary function)

指纹识别源代码。思路完全是按照文件夹中网页里介绍的方法，即提取指纹中的分叉点和端点的位置作为指纹的特征值。由于今天太忙，对图像的预处理作的很失败，程序会提取出很多伪点，而指纹轮廓也没有想出办法过滤。汗，你看看能不能参考把。 三个m文件，fd.m提取指纹中的分叉点，fd2.m提取指纹中的端点，Cpoint.m则是前两个文件运行中需要调用的掩模函数。(fingerprint identification code. Thinking is entirely in accordance with the folder on the website Lane, that the fingerprints of the bifurcation point and endpoint position as a fingerprint eigenvalues. As today are too busy, the image preprocessing for the failure, the program will extract a lot of pseudo-point, and the fingerprint profile nor find a way to filter. Khan, you can look at the information put. 3 m documents, fingerprints fd.m the bifurcation point, fd2.m fingerprints of endpoint, Cpoint.m are two documents before the operation need to call the mask function.)

信号在采集和输送过程中往往会参杂着噪声和干扰，将自适应神经网络与信号处理结合起来，采用最小均方（LSM）算法设计的线性自适应滤波器将信号中的杂波成分滤除。用matlab进行仿真,证实线性自适应滤波器具有良好的滤波功能。(Signal acquisition and delivery process often mingled with the noise and interference, the adaptive neural network combined with signal processing, with a minimum mean square (LSM) linear adaptive filter algorithm designed to signal noise filter components In addition. Using matlab simulation confirms linear adaptive filter has a good filtering.)

产生M序列并求其自相关，以及矩形成形和SA函数成形时的自相关(M sequency)

Computes Greenwich mean sidereal time from Julian Date

Clustering of information entropy classification algorithm(聚类信息熵分类算法Clustering of information entropy classification algorithm)

永磁同步电机的MATLAB模型,Clark变换，park变换仿真，及其逆变换 同步旋转坐标系下的数学建模 精致坐标下的数学建模(MATLAB model, Clark transform, park transform simulation and inverse transformation of permanent magnet synchronous motor (PMSM). Mathematical modeling in synchronous rotating coordinate system Mathematical modeling in refined coordinates)

％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)

Just a few functions used in my other toolboxes, for computing MSE and PSNR and some other less common image quality metrics.

Unit commitment and economic load dispatch by dynamic programming