rgbtogray

Matlab函数edge：边缘检测.输入灰度图像，返回同样大小的二值边缘图像(Matlab function edge: edge detection. Input gray image, return to the same size of the binary edge image)

this source code is transormers 2 code

通信中的QPSK相位调制建摸，其中考虑了多径和高斯的影响(Communication QPSK modulation phase modeling, which takes into account the multi-path effects and Gaussian)

说明：  KNN分类练习，有100数据，进行简单的KNN练习(KNN classification exercise, 100 data, simple KNN exercise)

有限元方法求解laplace 方程(matlab),可以用混合单元，混合边界条件(sloving Laplace eauations with finite element methods. )

基于铌酸锂MZ调制器，通过展开，计算其三阶互调失真以及SFDR等(Based on lithium niobate MZ modulator, by expanding to calculate the third-order intermodulation distortion and SFDR etc.)

haar特征的提取，包括六种haar特征，再别人代码的基础上改进的，希望对大家有帮助。(haar feature extraction, including the six the haar characteristics, and the code of others on the basis of improvement, we hope to help.)

模型预测控制算法由于采用了多步预测、滚动优化和反馈校正等控制策略，因而具有控制效果好、鲁棒性强、对模型精确性要求不高的优点。 希望对相关人有帮助(Model predictive control algorithm using a multi-step prediction , rolling optimization and feedback correction, control strategies, and thus has good control effect , the robustness of the model accuracy and less demanding . Related people)

各类CS的仿真 包括BP OMP COSAMP SL0 FOCUSS MMV-FOCUSS(All types of CS simulation include BP OMP COSAMP SL0 FOCUSS MMV-FOCUSS)

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)