madhirar1988

利用非数NaN对所选图像进行镂空、透视、剪切处理。(few NaN using non-selected images of Pierced, perspective, shear processing.)

power system tool box

Genetic Algorithm code

用matlab编程工具，编写具有操作界面的应用程序，通过菜单、对话框，选项框等界面控制，对算法进行演示。需要在应用系统中实现的算法及功能包括： 1、图像增强算法 （1）灰度线形变换：亮度及对比度可以调节（通过控制参数的改变，能够实时预览变化结果）； （2）直方图均衡：可在界面上对比均衡前后的效果。 2、图像变换算法 （3）对一幅彩色图像进行DCT变换和反变换，对比结果和原图； （4）仅保留左上角16X16的DCT系数，进行反变换，计算结果图的信噪比SNR。 3、图像分割算法 （5）采用最优阈值算法对灰度图像进行分割； （6）用Canny算法对灰度图像进行边缘检测； （7）用hough变换，检测边缘图像中的直线，并用不同颜色将检测出的直线叠加显示到原图像上。 (Preparation of a user interface with Matlab programming tools, applications, menus, dialog boxes, option boxes and other interface control, the algorithm demo. Algorithms and functions that need to be achieved in the application system including: 1, the image enhancement algorithm (1) gray linear transformation: the brightness and contrast can be adjusted (by controlling the change of the parameters, it is possible to real-time preview changes result) (2) Histogram equalization : contrast before and after equalization effect in the interface. 2, an image transformation algorithm (3) for a color image DCT transform and inverse transform, comparing the results and the original (4) to retain only the upper left corner of 16x16 DCT coefficient, the inverse transform, the signal-to-noise ratio SNR calculation results of FIG. . 3, image segmentation algorithm (5) The optimal threshold algorithm to gray-scale image segmentation (6) Canny algorithm for edge detection of gray-scale images ()

本程序基于MATLAB仿真工具实现主分量分析(The program is based on MATLAB simulation tools principal component analysis)

simulink and matlab7

现代通信系统（matlab版）（第二版）配套源代码 John G. Proakis等著 刘树棠 译 电子工业出版社出版(modern communication system (Matlab version) (2nd Edition) source code supporting John G. Proak Liushutang is waiting for the translation of the electronics industry published)

空间风场模拟程序，采用谐波平衡法模拟大气边界层(code for simulation of wind field of boundary layer.)

本程序采用MATLAB编程，主要用于GPS/INS组合导航的卡尔曼滤波算法研究。(matlab，GPS/INS，kalman )

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.