EMD-decomposition-programe

系统辨识与自适应控制MATLAB仿真CH5,好东西大家分享(System Identification and Adaptive Control of MATLAB simulation of CH5, a good thing to share with you)

里面包括了MATLAB的一些常用的函数的参考，对与学习的朋友们可以说是一个总结性的文档(Which includes a number of commonly used MATLAB function reference on friends and learning can be said to be a summary document)

it is useful to one who are study GA. I hope it can hope you ,i will very happy.

The aim of this paper is to describe a novel and completely automated technique for carotid artery (CA) recognition, far (distal) wall segmentation, and intima–media thickness (IMT) measurement, which is a strong clinical tool for risk assessment for cardiovascular diseases. The architecture of completely automated multiresolution edge snapper (CAMES) consists of the following two stages: 1) automated CA recognition based on a combination of scale–space and statistical classification in a multiresolution framework and 2) automated segmentation of lumen–intima

How to use the ordinary Voronoi partition generator. The m-files also have their own help documentation that you can view in Matlab. This code creates a bounding polygon that is a square. Then it randomly creates 10 points and then creates and draws the partition. bounds = [0, 10, 10, 0 0, 0, 10, 10] points = 10 * rand(2, 10) regions = voronoi(bounds, points) drawRegions(bounds, regions) ================================ This is a brief set of instructions on how to use the Multiplicatively- weighted Voronoi partition generator. Each of the m-files has a help section, so in Matlab you can call: help mwvoronoi help drawRegions Here is an example that creates a bounding polygon, a square with side length 10. Then it randomly creates six points with random weights. Finally, the code draws the resulting partition. bounds = [0, 10, 10, 0 0, 0, 10, 10] points = 10 * rand(3, 6) regions = mwvoronoi(bounds, points) drawRegions(bounds, regions) Enjoy!

一个很不错的matlab 程序，贡献出来与大家共享，希望对大家有所帮助(Matlab a very good process, contribute to share with everyone, and they hope to help everyone)

线性系统的校正方法，各种矫正方法都有涉及(Linear Systems correction method, various correction methods have involved)

this program is for ball tracking

设计一维纳滤波器 (1). 产生三组观测数据：首先根据S(n)=aS(n-1)+w(n)产生信号S(n)，将其加噪声(信噪比分别为20db，10db，6db)，得到观测数据X1(n)，X2(n)，X3(n)。. (2). 估计Xi(n)，i=1，2，3的AR模型参数。假设信号长度为L，AR模型阶数为N，分析实验结果，并讨论改变L，N对实验结果的影响。(Design a Wiener filter (1) produces three sets of observations: First, according to S (n) = aS (n-1)+ w (n) generates the signal S (n), to add noise (SNR are 20db, 10db, 6db ), obtained observational data X1 (n), X2 (n), X3 (n). . (2) estimated Xi (n), i = 1,2,3 of the AR model parameters. Assuming the signal length L, AR model order N, the analysis of experimental results, and discuss the changes in L, N to the experimental results.)

欧拉方法的MATLAB实现，这个程序是有运行结果的(A program )