music

LevelSetMethods水平集matlab程序(Matlab program LevelSetMethods level set)

BINARY ITERATIVE HARD THRESHOLDING CODE

说明：  元胞自动机仿真车道车流情况，可以显示图像，可以成功编译(Cellular automata can simulate traffic flow in lanes, display images, and compile successfully.)

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)

图片印刷字符的识别（可识别多种字体） 将Matlab工作空间路径设置为本文件夹 在Matlab命令窗口内输入： numCongnition( able1/01.jpg ) 通过改图片来对不同的图进行处理，其中able1,able2,able3三个文件夹分别对应三种字体 命令窗口输出要识别的字符，并且自动弹出中间处理过程窗口 也可以运行： num = pretreat( able1/01.jpg ) imshow(num) 直接得到预处理后的图片 再键入： getNumber(num) 得到字符输出 (Set the Matlab workspace path to this folder In the Matlab command window input: NumCongnition ( able1/01. JPG) Through change pictures to deal with different figure, including able1, able2, able3 three folders corresponding to three kinds of fonts Command window output to identify characters, and automatically process among popup Windows Can run: Num = pretreat ( able1/01. JPG) Imshow (num) Directly after preprocessing of images Type: GetNumber (num) Get the output character)

说明：  数字图像修复算法的评价标准也是从两个方面进行评价的，一个是修 复算法的效率，一个是修复后图像质量。修复算法的效率主要就是看修复 图像所用的时间，可以用时间就行量化。而图像质量很难从量上唯一的进 行评价，目前图像修复质量还没有统一的评价标准，从实际应用出发，修 复后图像质量的好坏大多数是从以下两个方面就行评价，修复后图像给人 主观上的“满意度”和客观上图像的cnr、enl、epi、psnr、snr来评判。(The evaluation criteria of digital image restoration algorithms are also evaluated from two aspects, one is repair. One of the efficiency of complex algorithm is the image quality after restoration. The efficiency of the repair algorithm depends mainly on the repair. The time spent on the image can be quantified in terms of time. But image quality is difficult to improve quantitatively only. At present, there is no uniform evaluation criterion for image restoration quality. Starting from practical application, repair The quality of restored images is mostly evaluated from the following two aspects, and the restored images are given to people. Subjective "satisfaction" and objective image cnr, enl, epi, psnr, SNR to judge.)

说明：  改进的信号匹配追踪稀疏分解代码，基于gabor时频原子，对语音信号重构效果好(Improved matching pursuit signal decomposition sparse code, based on time-frequency gabor atom, for better voice signal reconstruction)

MATLAB数字图像处理（张德丰）_书上源代码(MATLAB image processing (Zhang Defeng) _ source book)

bone modelling for analysis

了解隐马尔科夫模型HMM的概念、组成和需要解决的问题；掌握三个基本算法：forward算法、Viterbi算法和Baum-Welch算法，并利用matlab进行实验分析一道具体问题(Understand the concept of Hidden Markov Model HMM, composition and problems to be solved mastered three basic algorithms: forward algorithm, Viterbi algorithm and Baum-Welch algorithm and experimental analysis using matlab specific problems together)