Matlab2010--course

电力系统分析 随书光盘 源代码， MATLAB编写，有参考价值(CD-ROM with the book Power System Analysis)

实现测量坐标转换，主要有三参数、四参数、六参数、七参数以及二维坐标与三维坐标的转换(Measuring coordinate conversion, there are three parameters, four parameters, six parameters, seven parameters, and the conversion of two-dimensional coordinates and 3D coordinates)

一本matlab rune教材，有很多实例，比较简单，学习过程中可以不断尝试。(A book about matlab,it can be used by those who knows little about matlab.)

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)

MATLAB7.0 中的模拟仿真软件Simulink 仿真设计AM、DSB、SSB调制与解调系统。完成调制信号分析，并绘制相关的波形图及频谱图。(The simulation MATLAB7.0 simulation software Simulink design AM, DSB, SSB modulation and demodulation system. Complete modulation signal analysis, and draw the waveform and spectrum diagram related figure.)

一级倒立摆系统采用极点配置的方法控制，使其达到平衡状态(Inverted pendulum system using pole placement methods to control, to reach the equilibrium state)

This one is code for Random Forest algorithm,,,hav loaded face with FERET database,,,,,,,,,,,,,,,,,,,,,,,,,,,,

一个关于最速法的，matlab程序。经试验，效果很好。(A law on the most speed, matlab program. After testing, the effect is very good.)

face recognition very easily understandable..........u.....

基于星座图的QAM16仿真，易于理解QAM16的原理(QAM16 constellation simulation-based, easy to understand the principles of QAM16)