包含好几个合成地震记录的程序

图像模板匹配算法用MATLAB来试验，有例子大家可以看看，有上占还不完好，有能力的自己改改(Image template matching algorithm using MATLAB to test, there are examples we can see, there are not well accounted for, the ability of their changed)

RLS与LMS算法分析及比较，经调试可用。(RLS and LMS algorithm analysis and comparison, the debugging is available. )

kalman filter通熟易懂，可以快速理解卡尔曼滤波器的原理(kalman filter through the familiar and easy to understand, you can quickly understand the principle of the Kalman filter)

张正友摄像机标定matlab程序，用来求出摄像机的内外参数矩阵。(Zhang Zhengyou camera calibration matlab procedures used to calculate the camera' s internal and external parameter matrix.)

Blood vessel segmentation for fuzzy and edge detection which is uesd to detect the blood vessels and find edges

说明：  实验4 基于MATLAB的数字滤波器设计 有效的设计IIR和FIR滤波器(Experiment 4 MATLAB-based digital filter design effective design IIR and FIR filters)

一本较好的用MATLAB实现图像处理的书，有基础知识和实际例程(a better MATLAB image processing, and a basic knowledge of the actual routines)

基于matlab的非线性方程组求解的方法(Matlab-based non-linear equation solving methods)

％ 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)

在雷达和声纳的信号设计中，经常用的模糊函数，本程序给出了传统信号的模糊函数及仿真结果，适用于MATLAB初学者。(Sonar and radar signal design, often using the fuzzy function, this procedure gives the traditional signal ambiguity function and simulation results, suitable for beginners MATLAB. )