TC

应用matlab实现基于遗传算法的图像处理问题(Application of matlab genetic algorithm based on image segmentation)

Simulation of single phase fully controlled rectifier

复杂网络中基于谱分析的社区发现算法中，求解拉普拉斯矩阵的第二特征值（费德勒向量）代码(Spectral analysis of the complex network of community-based discovery algorithm for solving Laplace second eigenvalues ​ ​ of the matrix (Federer vector) code)

说明：  里面包含各种自适应算法，涉及多本不同的自适应书籍原文代码，可用于aec等等。(acoustic echo cancellation)

used for random deployment of nodes in wsn.

说明：  很经典的关于计算ＤＯＡ的算法——music算法，也是所有计算DOA的基础算法(Classic DOA on the calculation algorithm- music algorithm, is also the basis for all calculations DOA algorithm)

it presence the effect of stiffness variation in active air_suspension system.

[自動控制] Routh-Hankel matrix數值計算工具，輸入System Function後，程式會計算Hankel singular values and vectors、Schmidt pairs等值。詳情請見英文描述。(<<singular values and vectors>> [R_G,Sigma,U,V,Us,Vs]=HANKEL3(G) computes the Routh-Hankel matrix, the Hankel singular values and vectors, the Schmidt pairs of a given proper stable system G (created with either TF, ZPK, SS, or FRD).|| Output "R_G" is the Routh-Hankel matrix. || Output "Sigma" is a matrix whose elements on the diagonal are the Hankel singular values of the given system. || Output "U" is a matrix, the ith column of which is the left singular vector corresponding to the ith singular value. || Output "V" is a matrix, the ith column of which is the right singular vector corresponding to the ith singular value. || Output "Us" and "Vs" provides the Schmidt pairs. The ith elements of Us and Vs form the Schmidt pair corresponding the ith Hankel singular value. )

GMDH_main为GMDH主函数； variable_Combin为输入层初始变量选为x1,x1^2,x1*x2,x2^2,x2时的输入变量矩阵值 variable_select计算X_train训练输入数据,Y_train训练输出数据,X_test测试输入数据,Y_test测试输出数据 Combin为求变量的两两组合 Sym_Combin为求符号变量的两两组合 PE_AIC求每层各神经元的参数估计W，及训练数据在参数估计后估计的输出out_train，测试数据在参数估计后的估计输出out_test，还有与实际比较的误差平方和PESS， 以及准则值AIC sym_representation求最终的输入输出符号表达式 Criterion_value求准则值 (GMDH_main main function for the GMDH variable_Combin initial variables chosen for the input layer, x1, x1 ^ 2, x1* x2, x2 ^ 2, x2 the value of the input variable matrix calculation X_train variable_select training input data, Y_train training output data, X_test test input data, Y_test for the sake of the test output data Combin pairwise combination of variables for the sake of symbolic variables Sym_Combin pairwise combinations PE_AIC neurons find each parameter estimation of the W, and after the training data is estimated in the estimation of output out_train, test data After the parameter estimates of the output estimated out_test, also compared with the actual sum of squared errors PESS, as well as the final criterion value AIC sym_representation seek the input and output values ​ ​ of symbolic expressions Criterion_value find criteria)

使用matlab编写遗传算法，解决车辆路径最优化问题。(VRp using GA methods)