hundun

基于密度的算法dbscan，matlab程序(Dbscan algorithm based on density, the matlab program)

马尔科夫蒙特卡洛，通过MH算法对初始状态和状态转移矩阵进行预测(Markov Chain Monte Carlo, by MH algorithm to the initial state and the state transition matrix to predict)

电力系统潮流计算，matlab编程，适合电力系统大三大四学生课程设计(Power flow calculation system )

基于IEEE14节点牛顿——拉夫逊潮流计算原代码，计算简单，收敛迅速。(14 node power flow calculation, Newton - Raphson power flow calculation, the calculation is simple, rapid convergence)

通过对视频的适当修改，运用matlab软件实现视频图片提取。(chang video into image with matlab)

数学建模实验&matlab实现求矩阵特征值特征向量AHP方法的建模与实现 计算矩阵特征值、特征向量；AHP方法的建模与实现 数学建模实验&matlab实现求矩阵特征值特征向量AHP方法的建模与实现(Experimental & matlab implementation of mathematical modeling to evaluate matrix eigenvalue eigenvector method of AHP Modeling and Implementation of calculating matrix eigenvalues, eigenvectors AHP method of modeling and implementation to achieve mathematical modeling experiments & matlab Matrix Eigenvalues and Eigenvectors AHP method of construction Model and Implementation)

matlab命令表包含很多各种操作命名，这样在我们需要的时候简单方便查用。(The matlab command tabel contains a lot of commands of matlab which is easy for us to look for when necessary.)

qpsk调制解调 源文件，在现在的毕业设计和课程设计中都有要求的(modem qpsk source file, in the current school design and curriculum design have requested)

无线传感器网络连通问题 其中点的测试matlab程序(Wireless sensor network connectivity issues which point the test matlab program)

％ 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)