mars1-5

随机介质的模型建立，用于地震波模拟的研究！(Random medium model, used in seismic wave simulation research!)

Modelling and Control of a Three-Phase Four-Switch PWM-VSR in d-q Synchronous Frame

关于MATLAB图形用户界面(GUI)初学者指导教程系列，有较详细的说明和指导(On the MATLAB graphical user interface (GUI) Beginners Guide series, has a more detailed explanation and guidance)

stamp 算法，用于解超大规模电路方程(stamp algrithm, used for solving large ciucuit equation.)

本程序的功能是用牛顿－拉夫逊法进行潮流计算(This program function is to use Newton- rafer Johnson flow calculation method.)

programme matlab dvb-s tool

this code gives minimum peak to average power ratio. the technique used here is adding peak reduction carriers

To calculate gravitation field between moon and earth using charge simulation methods

观测星表的制备，通过对第谷星表的筛选，选出合适的星体，是星敏感器的重要组成部分，适合刚刚接触的人很快进入状态(Preparation observation catalog, through the screening of Tycho catalog, choose the right stars, is an important part of the star sensor, for just contact people quickly enter the state)

％ 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)