PN

Control of stepper motor using matlab.

logistic映射分岔图的四种实现方法(logistic map bifurcation diagram of the four implementations)

mathlab的三个分别灰色绝对关联度，相对关联度，归一关联度的代码，是三份M文件(mathlab absolute correlation of the three were gray, relative correlation, normalized correlation of the code, the file is three M)

模态参数识别ERA方法的源代码，可利用该方法进行环境激励下结构模态参数识别。(modal parameter identification ERA method of source code, The method can be used for environmental inspired modal parameter identification.)

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)

比较了几种经典的LMS自适应滤波算法，很清楚地看出在低信噪比下各算法的性能( It compared several classical LMS adaptive filtering algorithm,)

ARIMA交通流预测程序，利用perms上的数据进行预测(ARIMA traffic flow prediction program)

SVPWM控制的有源滤波器matlab simulink仿真(Matlab Simulink simulation of active filter based on SVPWM control)

LMNN,监督距离度量学习目前效果最好的(lmnn)

产生一个各项均匀的多维的光学点扩散函数模型的matlab m 文件！！！(Produce a uniform multidimensional various optical point spread function model matlab m file! ! !)