agoodsourceuwb

ofdm simulation for BER performance

用scilab（和matlab一样，只是非常小）实现希尔密码的加密与解密(With scilab (and matlab, only very small) the achievement of Hill of encryption and decryption)

MATLAB在图像处理中的应用，七个文件，适合图像处理初学者使用，原创。(MATLAB in image processing applications, the seven files, suitable for beginners to use image processing, originality.)

Multiple-Instance Learning for Weakly Supervised Object Categorization

code matlab descripteur gist matlab

说明：  本文提出了一种基于混沌加密的DCT域二值图像数字水印算法.该算法首先利用混沌序列将含有版权信息的有意义二值图像水印进行加密,然后利用人眼视觉系统(HVS)的特性将原始载体图像进行块分类,最后将不同强度的水印分量嵌入到不同类的图像块DCT中频系数中去.利用混沌序列对水印进行加密,使水印本身具有安全性,对数字作品进行双重保障.通过高斯噪声,椒盐噪声以及JPEG压缩和剪切等攻击试验,表明了该算法具有较好的鲁棒性.(Encryption in DCT domain is proposed. Firstly, the meaningful binary image watermark containing copyright information is encrypted by using chaotic sequence, and then the original image is classified by using the characteristics of human visual system (HVS), Finally, the watermark components with different intensities are embedded into the DCT intermediate frequency coefficients of different types of image blocks. Chaotic sequences are used to encrypt the watermark, so that the watermark itself has security and double protection for digital works. Experiments on Gaussian noise, salt and pepper noise, JPEG compression and clipping show that the algorithm has good robustness)

本程序在MATLAB开发环境下，用周期图谱估计的方法对信号的频谱进行了估计，估计结构为两个频率分量。(The procedure developed in the MATLAB environment, with the cycle map estimation method to estimate the signal s spectrum, estimated structure for the two frequency components)

This code implements a variety of ways to solve sparse constraint solution

matlab 关于association rule 的自己写的函数，有3个文件, association.m：h = association(m, i, j) i=>j, m是数据，h是support和confidence，该函数只适用于单个数据 ass_item: h=ass_itset(m, a, b) 同上，但是可用于多个数据（m为数组） assrule: h = assrule(m, threshold1, threshold2) 该函数用于classification， 得到规则，threshold1为要求的support,threshold2为要求的confidence，h 则为符合要求的规则及其support和confidence，前2列为规则，后2列为其support和confidence (matlab on the association rule to write functions, there are 3 files, association.m: h = association (m, i, j) i => j, m is the data, h is the support and confidence, this function applies only to a single Data ass_item: h = ass_itset (m, a, b) it is the same as above, but it can be used for multiple data (m can be matrix) assrule: h = assrule (m, threshold1, threshold2) the function used for classification,get the rules, threshold1 is the require of support, threshold2 is the required of confidence, h is the rules and their support and confidence, the former two columns as a rule, the latter two columns as one of its support and confidence)

matlab 的常用算法源代码，包含插值拟合/规划/方程求解等多个代码(matlab source code for commonly used algorithms, including interpolation fitting/planning/equations and other codes)