Cours_Matlab-P17

先进PID控制MATLAB仿真（第3版）/刘金琨-第四章中的仿真程序(Advanced PID control MATLAB (version 3)/Liu Jinkun- of Chapter IV of the simulation program)

用fleury算法计算一个欧拉图的穷举的方法 注意：w代表欧拉图矩阵 begin代表起点 只能是欧拉图！(Fleury algorithm using an exhaustive method of Euler diagram Note: w on behalf of the Euler diagram can only be a starting point matrix begin on behalf of the Euler diagram!)

这个主要是我所做的一段matlab代码，主要实现剖面上的数据在平面上求解的过程(this I was doing a Matlab code, main profile in the data plane for the course)

七单元天线阵MUSIC DOA估计： d=1 ， 天线阵元的间距； lma=2， 信号中心波长； 四输入信号； A=[A1,A2,A3,A4]， 得出A矩； 四信号的频率d=[1.3*cos(v1*n) 1*sin(v2*n) 1*sin(v3*n) 1*sin(v4*n)] 构造输入信号矢量 U=A*d 总的输入信号 总输入信号的协方差矩阵 [s,h]=eig(c) 求协方差的特征矢量及特征值 取出与零特征值对应的特征矢量 求协方差矩阵的逆矩阵 应用Music法估计输出 绘出各波达方向图(Seven-element antenna array MUSIC DOA estimates: d = 1, Antenna Array pitch LMA = 2 signal center wavelength four input signals A = [A1, A2, A3, and A4], drawn A moment tetra-frequency of the signal D = [1.3* cos (V1* n) 1* ⁢ sin (v2* n) 1* sin (v3* n) 1* sin (V4* n)] constructed input signal vector U = A* D of the total input signal of the total input signal covariance matrix [S] = EIG (c) seeking covariance feature vector and the feature value removing and corresponding to the zero eigenvalues ​ ​ characterized vector seeking covariance matrix inverse matrix Applications Music estimate output plotted DOA Figure)

教你如何根据一副RGB图像创建出一幅灰度图像，并将它们显示在屏幕上面(Teach you how to create a grayscale image according to an RGB image, and displays them on the screen above)

depelopment research on watermarking

二进制编码的遗传算法源程序，可以对此算法进行改进，编写出自己需要的程序(Binary-coded genetic algorithm source code, you can improve on this algorithm, write out the procedures they need)

deal with matlab soure for matlab toolbox

地质雷达仿真软件，可以模拟各种结构，得到仿真数据。可编程也脚本文件(Geological radar simulation software can simulate a variety of structures, to get the simulation data. Programmable also script file)

可以求解系统的亚谐波共振,例如求解轧机振动系统的1/3亚谐波共振(You can solve the sub-harmonic resonance system)