Simulation_FOC

说明：  自适应控制使用李雅普诺夫推导自适应律的学习程序(Adaptive control uses Lyapunov to derive adaptive law)

说明：  自相关函数求解代码，可以求取信号的自相关函数(Autocorrelation function to solve the code, you can strike a signal autocorrelation function)

wireless sensor network time synchronization based on TPSN and RBS

电弧炉神经网络预测控制，三相。解耦控制，效果明显(Neural network predictive control of electric arc furnace, three-phase. Decoupling control, the effect is obvious)

Lagrange插值、Newton插值函数等插值函数，函数为数值分析课本上的例题。(Lagrange interpolation, Newton interpolation function, such as interpolation function, function for the numerical analysis of the textbooks on the sample questions.)

Contemporary optical image processing with matlab

To estimate the input-output mapping with inputs x ％ and outputs y generated by the following nonlinear, ％ nonstationary state space model: ％ x(t+1) = 0.5x(t) + [25x(t)]/[(1+x(t))^(2)] ％ + 8cos(1.2t) + process noise ％ y(t) = x(t)^(2) / 20 + 6 squareWave(0.05(t-1)) + 3 ％ + time varying measurement noise ％ using a multi-layer perceptron (MLP) and both the EKF and ％ the hybrid importance-samping resampling (SIR) algorithm. (To estimate the input-output mapping with inputs x and outputs y generated by the following nonlinear, nonstationary state space model: x (t+ 1) = 0.5x (t)+ [25x (t )]/[( 1+ x (t)) ^ (2)]+ 8cos (1.2t)+ process noise y (t) = x (t) ^ (2)/20+ 6 squareWave (0.05 (t-1 ))+ 3+ time varying measurement noise using a multi-layer perceptron (MLP) and both the EKF and the hybrid importance-samping resampling (SIR) algorithm.)

1、工具箱：LS_SVMlab Classification_LS_SVMlab.m - 多类分类 Regression_LS_SVMlab.m - 函数拟合 2、工具箱：OSU_SVM3.00 Classification_OSU_SVM.m - 多类分类 3、工具箱：stprtoolsvm Classification_stprtool.m - 多类分类 4、工具箱：SVM_SteveGunn Classification_SVM_SteveGunn.m - 二类分类 Regression_SVM_SteveGunn.m - 函数拟合 (a toolbox : LS_SVMlab Classification_LS_SVMlab.m-over classification Regression_LS_SVMlab.m-function fitting 2, toolbox : OSU_SVM3.00 Classification_OSU_SVM.m-over classification 3, toolbox : stprtool svm Classification_stprtool.m-over category Categories 4, toolbox : SVM_SteveGunn Classification_SVM_SteveGun n.m-II classification Regression_SVM_SteveGunn.m-fitting function)

离散傅立叶变换程序及希尔伯特变换程序，希尔伯特变换对于信号变换有重要意义。该程序通过验证，效果理想。 (Hilbert transfer program)

Implementation of K-MEANS classification of 2D data of this code, the high speed