eigenvalue_p1_2D

UCI 上面的经典数据 UCI 上面的经典数据UCI 上面的经典数据(UCI data)

nonmaxsup——非最大值抑制 hysthresh——设定阈值区间，返回一个二值化图像 canny——边缘探测，图像边缘增强 adjgamma——调整图像的伽马值 findline——利用线性Hough变换和Canny边缘探测得到的线上各点的坐标 circlecoords——返回由圆的半径和圆心坐标决定的圆上各点像素的坐标 houghcircle——取一幅经过canny变换的图像，利用hough变换找到图像中的一个圆 findcircle——计算所得线上各点的坐标归纳出一个圆的半径和圆心，确定该圆的各点坐标 gaborconvolve——利用一维盖伯滤波器对图像进行处理 gethammingdistance ——返回两幅虹膜图像提取的特征码之间的海明距离 linecoords——返回一条线的上各点的x,y坐标值(nonmaxsup- non-maximum suppression hysthresh- set the threshold range, returns a binary image canny- edge detection, image edge enhancement adjgamma- adjust the image' s gamma value findline- linear Hough transform and Canny edge detection get the coordinates of each point circlecoords online- Returns coordinate houghcircle on the circle of the radius and center coordinates of the points decision pixels- After taking a picture canny transformation, using hough transform to find the image of a circle findcircle- the calculated coordinates of each point line summed up a circle of radius and center, to determine the coordinates of each point of the circle gaborconvolve- using a 维盖伯 filter for image processing gethammingdistance- returns two iris images extracted linecoords Hamming distance between the signature- a return line to the points on the x, y coordinate values)

现代数字信号处理 何广军 MATLAB 代码(MATLAB code of digital signal processing edited by Hu GuangJun)

这是一个SVM的故障诊断应用程序，利用MATLAB可以直接运行程序(This is a SVM for fault diagnosis application, use of MATLAB can run programs)

Matlab编程学习资料，对初学者有帮助。。。(Matlab programming to learn information useful for beginners. . .)

亚式期权和欧式期权的一篮子组合以及策略测试(Asian options and European options on a basket of portfolio and strategy testing)

Digital television system

用matlab编写的一串算法基本框架，可以自行在该代码中编写自己的程序，实现一定功能(Algorithm using matlab basic framework of a string, you can write the code on their own in their own procedures to achieve a certain function)

MATLAB7.x数字信号处理，基本的数字信号处理的程序都在这里了(nearly all the DPS program)

The fusion of images is the process of combining two or more images into a single image retaining important features from each of the images. A scheme for fusion of multi-resolution 2D gray level images based on wavelet transform is presented in this paper. If the images are not already registered, a point-based registration, using affine transformation is performed prior to fusion. The images to be fused are first decomposed into sub images with different frequency and then information fusion is performed using these images under the proposed gradient and relative smoothness criterion. Finally these sub images are reconstructed into the result image with plentiful information. A quantitative measure of the degree of fusion is estimated by cross-correlation coefficient and comparison with some of the existing wavelet transform based image fusion techniques is carried out.