mmm

说明：  此模型实现了两电平的PWM无源逆变，且功率因数可调。(This model is realizedthe Two level source inverter power and the factor can be adjusted.)

flexible job shop 使用基因演算法解柔性作業車間調度問題(flexible job shop Using genetic algorithm to solve flexible job shop scheduling problem)

A program that calculates charge distribution on parallel plate capacitor using MOM(method of moments) method and matlab language this program uses a 3d model of space between plates.

This is a complete program for speaker recognition based MATLAB. It uses VQ(vector quantization) method to detect different speakers.

说明：  matlab CIC滤波器程序,5级CIC滤波器的设计,采用优化结构，采样速率在积分器后降低；(matlab CIC program,five taps design.)

说明：  matlab 功能工具 matlab 功能工具(matlab functions matlab function tool tool)

国外著名控制专著《extremum seeking control and application》第6章案例matlab源码(matab code for examples of ch6 in a well-known book《extremum seeking control and application》)

使用matlab进行多径效应的仿真。直接运行主函数即可(Matlab simulation of multipath effects.)

It is matlab code for object detection

统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含： 1，Analysis of linear discriminant function 2，Feature extraction: Linear Discriminant Analysis 3，Probability distribution estimation and clustering 4，Support Vector and other Kernel Machines( This section should give the reader a quick overview of the methods implemented in STPRtool. • Analysis of linear discriminant function: Perceptron algorithm and multiclass modification. Kozinec’s algorithm. Fisher Linear Discriminant. A collection of known algorithms solving the Generalized Anderson’s Task. • Feature extraction: Linear Discriminant Analysis. Principal Component Analysis (PCA). Kernel PCA. Greedy Kernel PCA. Generalized Discriminant Analysis. • Probability distribution estimation and clustering: Gaussian Mixture Models. Expectation-Maximization algorithm. Minimax probability estimation. K-means clustering. • Support Vector and other Kernel Machines: Sequential Minimal Optimizer (SMO). Matlab Optimization toolbox based algorithms. Interface to the SVMlight software. Decomposition approaches to train the Multi-class SVM classifiers. Multi-class BSVM formulation trained by Kozinec’s algorithm, Mitchell- Demyanov-Molozenov algorithm )