EEG_ECG_Matlab

说明：  IMPLEMENTATION OF ECONOMICAL DISPATCH

基于模型的压缩感知工具箱，MATLAB代码，内有相关文章(This package contains Matlab implementations of various CS recovery algorithms that have been developed using the framework described in the above paper。Each folder in the package essentially consists of a CS recovery algorithm based on a particular signal model, and a script that tests that recovery algorithm.)

这里实现了基于四种SVM工具箱的分类与回归算法: 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 更详细的相关函数说明请通过help命令查看！(Here the realization of the four SVM toolbox based on the classification and regression algorithm: 1, Toolbox: LS_SVMlabClassification_LS_SVMlab.m- Multiclass Classification Regression_LS_SVMlab.m- function fitting 2, the toolbox: OSU_SVM3.00Classification_OSU_SVM.m- Multiclass Classification 3, Toolbox: stprtoolsvmClassification_stprtool.m- Multiclass Classification 4 toolbox: SVM_SteveGunnClassification_SVM_SteveGunn.m- II Category Regression_SVM_SteveGunn.m- function fitting a more detailed explanation of the correlation function through the help command to view!)

说明：  机械工程设计中对于连杆机构的运动分析的相关程序(Mechanical Engineering Design movement for linkage analysis procedures)

image hiding introduction procedure

永磁同步电机位置传感器矢量控制Matlab程序 高频注入法(Permanent magnet synchronous motor position sensorless vector control program Matlab High frequency injection method)

卷积编码MATLAB仿真,Code Rate=1/2(Convolutional coding MATLAB simulation, Code Rate = 1/2)

本程序实现chebyshev I型低通滤波(the program chebyshev I-low-pass filter)

人工网络的原理及应用讲义。讲得很详细，包括matlab仿真方法(Principles of artificial network and application notes. Very detailed, including the matlab simulation method)

利用基于生理的情感神经网络，包含杏仁体，丘脑，视觉神经等重要元素，可用于分类与预测，性能优越于SVM(The use of neural network based on emotional physiology, contains important elements of the amygdala, thalamus, optic nerve, etc., can be used for classification and prediction, superior performance to SVM)