watermarking_mpeg2_research_paper

function g=distance_classify(A,b) 距离判别法程序。 输入已分类样本A（元胞数组），输入待分类样本b 输出待分类样本b的类别g 注：一般还应计算回代误差yita 输入已知分类样本的总类别数n 每类作为元胞数组的一列(function g = distance_classify (A, b) from the Criterion procedures. Input samples have been classified A (cell array), the importation of samples for classification b output samples for classification g categories b Note: the calculation should also be back on behalf of the general error input yita of the total known types of classification of the number of samples n each Cellular-type array as a)

说明：  this document about Brain waves alpha,beta,theta and delta and their frequencies range and how to detect them using any software labview and matlab

Matlab雷达工具箱，实现雷达信号处理的各种功能。(Matlab toolbox radar, radar signal processing implementation of the various functions.)

本书是一本数值线性代数的导论性著作，作者深刻阐述了数值代数的基本思想，加上他们清新、引人入胜的写作风格，使得本书成为本领域的经典之作(This book is an introductory numerical linear algebra book, the author expounded the basic idea of numerical algebra, together with their fresh, engaging writing style makes this book a classic in the field)

说明：  卷积交织卷积交织卷积交织卷积交织卷积交织卷积交织卷积交织(Convolution interweaveConvolution interweaveConvolution interweaveConvolution interweaveConvolution interweave)

matlaB GUI界面学习资料，包括界面编程，各种控件工具栏。菜单的使用(MATLAB GUI interface to learning materials, including the programming interface, a variety of controls toolbar. Use of the menu)

自适应算法滤波器--lms，以《现代信号处理》（张贤达）书上所讲过程所写(Adaptive algorithm filters- lms, to the "Modern Signal Processing" (Zhang XD) book written by the process of speaking)

说明：  EEG脑电信号处理，使用CSP提取特征，后使用极限学习机ELM进行模型训练和分类，有较高的正确率。(CSP processing and ELM classification of EEG data.)

It s a useful thing helping you to pragramming the finite element with matlab.

EM 算法是求参数极大似然估计的一种方法，它可以从非完整数据集中对参数进行估计，是一种非常简单实用的学习算法。这种方法可以广泛地应用于处理缺损数据、截尾数据以及带有噪声等所谓的不完全数据，可以具体来说，我们可以利用EM算法来填充样本中的缺失数据、发现隐藏变量的值、估计HMM中的参数、估计有限混合分布中的参数以及可以进行无监督聚类等等。(Expectation Maximization image segmentation Input: ima: grey color image k: Number of classes Output: mask: clasification image mask mu: vector of class means v: vector of class variances p: vector of class proportions )