Bayes

cycloconveter with scr commutation

常规声波波动方程正演程序，可动画演示,未做边界处理(acoustic equation wave forward modeling based on convention grid)

基于PCA的人脸识别的Matlab程序，详细代码，简单易懂(PCA-based face recognition Matlab procedures, detailed code, simple and easy to understand)

Contacts Settings Test extends Instrumentation Test Case.

本文是采用matlab开发的识别数字的识别软件，同时提供相应的样本数字图。(This article is developed using matlab digit identification recognition software, while providing the corresponding sample figures Fig.)

说明：  本程序可实现图像边缘检测后的短线段检测和连接(the short line will be detected and linked by using this programm)

simple ac transformer circuit

matlab simulation about DY5 transformer

基于wilson理论的200kw风力机叶片设计(Wilson law-based wind turbine blade design)

％ EM algorithm for k multidimensional Gaussian mixture estimation ％ ％ Inputs: ％ X(n,d) - input data, n=number of observations, d=dimension of variable ％ k - maximum number of Gaussian components allowed ％ ltol - percentage of the log likelihood difference between 2 iterations ([] for none) ％ maxiter - maximum number of iteration allowed ([] for none) ％ pflag - 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) ％ Init - structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none) ％ ％ Ouputs: ％ W(1,k) - estimated weights of GM ％ M(d,k) - estimated mean vectors of GM ％ V(d,d,k) - estimated covariance matrices of GM ％ L - log likelihood of estimates ％( EM algorithm for k multidimensional Gaussian mixture estimation Inputs: X (n, d)- input data, n = number of observations, d = dimension of variable k- maximum number of Gaussian components allowed ltol- percentage of the log likelihood difference between 2 iterations ([] for none) maxiter- maximum number of iteration allowed ([] for none) pflag- 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) Init- structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none) Ouputs: W (1, k)- estimated weights of GM M (d, k)- estimated mean vectors of GM V (d, d, k)- estimated covariance matrices of GM L- log likelihood of estimates)