sins4357345637456375

通过自适应算法来预测将来的变化。是通过matlab来实现的。已经调试完成(Through the adaptive algorithm to predict the future changes. Are achieved through matlab. Have been debug finish)

artifical neuro fuzzy logic

MATLAB初学者使用教程，共4部分。第1章概述1.rar第2章语法.rar第3章SIMULINK.rar第4章建模.rar(MATLAB Tutorial for beginners to use, a total of 4 parts. Chapter 1 outlines the 1.rar Chapter 2 grammar. Rar Chapter 3 SIMULINK.rar Chapter 4 Modeling. Rar)

Matlab code to load image, separate image component and determine PCA

DV-hop与min-max相结合，使得计算量更小，在最后对结果求精，定位精度更高。(DV- hop combined with min- Max, makes a smaller amount of calculation, at the end of the refinement, positioning accuracy is higher. )

Code implementation of a Multilayer Perceptron that learns the logical XOR function (for 2 and 4 inputs).

说明：  人工蜂群算法的matlab实现，智能启发式算法(artificial bee colony)

MATLAB语言完整命令代码集 (MATLAB language complete command code set)

PID调节器，可以通过调节PID参数观察曲线变化(PID controller, you can adjust the PID parameters observed curve)

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)