wavelet-packet

％ 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)

This Simulink model simulate GMSK modulatino in Rayleigh channel.

经优化后的xls文件导入到dbf文件的表单,dbf文件请自己创建(By importing the XLS file after the optimization to the DBF file form, please create your own DBF file )

its diodes study for current load and behavior of diodes simulink this to learning fro matlab

关于bp网络观察权值和偏差的变化情况小程序( bp network weights and deviations observed changes in the applet)

For using this code need to use signal toolbox and general toolbox in your matlab Inpainting using sparse regularization. Consider the pepper image with many missing pixels. Assume that the image is noisy-free. (a) Inpaint the image by using orthogonal wavelet sparsity. (b) Inpaint the image by using a different sparsity prior. Based on the outputs, it is clear that the inpainting result obtain by Sobolev is much better than other methods (i.e. Orthogonal wavelet sparsity and Invariant wavelet sparsity).

multi uav path planning for 2D

说明：  cstering in mtlb.to cstetring in

利用authorware制作的丽江旅游介绍，利用authorware的四种交互，对于初学者是一个较好的实用例子。(produced using authorware tourism on Lijiang, using authorware four interactive, for beginners is a good practical example.)

图像的拉普拉斯变换及其matlab代码实现及代码测试(Images of the Laplace transform and its matlab code implementation and testing )