ploting-images-in-matlab

自己编写的matlab微粒群算法工具箱。微粒群算法（pso）是一种人工智能算法，速度比遗传算法快一些。(I have written matlab PSO toolbox. Particle swarm optimization (pso) is an artificial intelligence algorithm, the speed faster than the genetic algorithm.)

这是一篇matlab模糊聚类方法分析的一篇例文，参考价值很大(This is a matlab fuzzy clustering analysis of a Liwen, a great reference value)

希尔伯特变换分析程序代码 采用EMD分解

说明：  这个是MATLAB实现Hough变换的程序。有基本的Hough变换的理解程序，也有使用Hough变换来检测信号的程序(This is the realization of Hough Transform MATLAB procedures. Hough transform a basic understanding of procedures, have also used the Hough transform to detect the signal process)

说明：  此文件夹主要是在学习自适应语音小波阈值去噪中所查找的文献，其中论文包括自适应算法的介绍、语音小波自适应去噪、其他数字信号自适应小波阈值去噪。(This folder is the main voice in the learning adaptive wavelet threshold denoising in the search of the literature, which includes adaptive algorithm thesis presentation, voice, wavelet adaptive denoising, and other digital signal adaptive wavelet thresholding.)

主要应用于两幅图片比对时，对两幅图片进行校准(Mainly used in the two pictures, two pictures calibration)

维也纳理工大学，LTE物理层链路仿真其中的信道估计模块的m语言代码(Vienna University of Technology, LTE physical layer link simulation in which the channel estimation module m language code)

用matlab解三对角方程，可应用在化工、电子、机械等工程领域。(Gaussian elimination method to solve tridiagonal equation)

％ 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)

Circular Hough_ Grd人眼定位的简单实现程序(Circular Hough_ Grd)