GMM

a presentation on understanding the matlab and simulink may be of someones help

we can use this file for compressive sensing

《visual c++matlab图像处理与识别实用案例精选》源码(" Visual c++ matlab image processing and recognition of practical cases selected" source)

MATLAB的gui指导，各种情况详细的代码(MATLAB-gui guide, the code in detail the various situations)

This program show how a deformed spectrum would affect the pulse shape

电压暂降正周期有效值,是四案例工程中比较常见的算法。(t=0:0.0002:0.2 y=cos(100*pi*t) y1=0.5*cos(100*pi*t) y(200:600)=y1(200:600) for i=1:1:901 u(i)=sqrt(sum(y(i:i+99).^2)/100) end plot(u) xlable( 采样点数 ) ylable( u ) )

海明加权的天线方向图，使用matlab 调试过，对研究雷达天线的同志很有帮助。(Hamming weighted antenna pattern, use the debug matlab, and the study of the radar antenna comrades helpful.)

这是一个基于颜色直方图的粒子滤波目标跟踪的主程序，比较完整，供大家参考(This is a color histogram based particle filter tracking the main program, more complete, for your reference)

MATLAB® is a high-level technical computing language and interactive environment for algorithm development, data visualization, data analysis, and numeric computation. Using the MATLAB product, you can solve technical computing problems faster than with traditional programming languages, such as C, C++, and Fortran. You can use MATLAB in a wide range of applications, including signal and image processing, communications, control design, test and measurement, financial modeling and analysis, and computational biology. Add-on toolboxes (collections of special-purpose MATLAB functions, available separately) extend the MATLAB environment to solve particular classes of problems in these application areas. MATLAB provides a number of features for documenting and sharing your work. You can integrate your MATLAB code with other languages and applications, and distribute your MATLAB algorithms and applications.

说明：  Edge detection result should be enhanced using linear method like Median filter to remove the garbage around the pupil to gain clear pupil to determine perfect centre. Get the centre of the pupil by counting the number of black pixels (zero value) of each column and row. Then get each row and column that has the maximum number of these black pixels. Then determine the center by simple calculation according to the image coordinate to set it correct on the image, consequently we can determine the radius of the pupil. Thus we can find the pupillary boundary (inner). A similar procedure is extended by using a coarse scale to locate the outer boundary (limbus) which can be apparent by using the mid-point algorithms of circle and ellipse.