Zernike-Polynomial-Coefficients-for-a-given-Wavef

GUIA DE AUTOAPRENDIZAJE PARA VISUAL BASIC

经典通信教材，移动通信原理，有吴伟陵，牛凯著写(Classical communication materials, mobile communication theory, there WU Wei-ling, cattle Kay of writing)

都市供求信息网分为前、后台两部分设计，前台主要实现信息的显示、搜索与发布功能，其中信息的显示包括列表显示与详细内容显示，而列表显示，又分为首页信息列表显示、查看某类别下所有信息的列表显示和搜索结果列表显示；搜索功能主要包括定位搜索和模糊搜索。后台主要实现的功能为信息显示、信息审核、信息删除、付费设置与退出登录，其中的信息显示功能也分为列表显示与详细内容显示。(Supply and demand information network before the city divided into two parts design background, foreground main achievement of the display, search and publishing of information, which displays information including a list of displays and display details, but the list is displayed, the information is divided into the Home display list, see Under a category displays a list of all the information and the search results list displays Search functions include positioning search and fuzzy search. The main function of the background information display, information auditing, information deleted, pay setting and exit the registry, which is also divided into the information display function displays detailed contents list display.)

基于MATLAB的数字音频水印技术程序，一种数字音频水印(MATLAB-based digital audio watermarking technology program)

6种信号的调制识别，识别率在SNR<10是高达90 。非常好的程序！！！(a very good matlab program!)

ant colony publications

以matlab实作histgram equalizatuin(To implement histgram equalizatuin matlab)

说明：  mATLAB CODE FOR gAUSSIAN KERNEL

this tutorial will help beginners in the radar image processing. The programs are arranged in form of the chapters. all the best.

说明：  半监督学习(Semi-Supervised Learning，SSL)是模式识别和机器学习领域研究的重点问题，是监督学习与无监督学习相结合的一种学习方法。半监督学习使用大量的未标记数据，以及同时使用标记数据，来进行模式识别工作。当使用半监督学习时，将会要求尽量少的人员来从事工作，同时，又能够带来比较高的准确性，因此，半监督学习目前正越来越受到人们的重视。(Semi-Supervised Learning (SSL) is a key issue in the field of pattern recognition and machine learning. It is a learning method combining supervised learning with unsupervised learning. Semi-supervised learning uses a large number of unlabeled data, as well as labeled data, for pattern recognition. When using semi-supervised learning, it will require as few people as possible to work, and at the same time, it can bring relatively high accuracy. Therefore, semi-supervised learning is receiving more and more attention.)