MATLABCompile

补码键控调制(CCK)算法及实现，包括补码的产生。可以计算补码的增益。主要用在802.11b中(Complementary Code Keying modulation (CCK) algorithm and implementation, including the emergence of complement. Complementary code can calculate the gain. Mainly used in 802.11b Medium)

algorithm for calculating sum of matrices

This is IP optimization method examples with constraints

说明：  比利时著名女数学家编写的小波十讲，小波分析经典教材。(The famous mathematician compilation of Belgium, wavelet and wavelet analysis of ten classical textbook.)

这是一个很好的控制台应用程序，可以方便的在其中添加模块。(This is a good console application, you can easily add modules where.)

The goal of Optical Character Recognition (OCR) is to classify optical patterns (often contained in a digital image) corresponding to alphanumeric or other characters. The process of OCR involves several steps including segmentation, feature extraction, and classification. Each of these steps is a field unto itself, and is described briefly here in the context of a Matlab implementation of OCR.

负荷预测One world, one dream, I only want to download your stuff. One world, one dream, I only want to download your stuff. (we are the world One world, one dream, I only want to download your stuff. )

说明：  因为经典粗糙集只能处理离散型数据，而连续性数据必须离散化才能处理，但是离散化可能会丢失部分重要信息，所有使用基于邻域粗糙集的属性约简去处理连续性数据。(Attribute reduction based on neighborhood rough set)

基于奇异值分解的人脸识别方法 梁毅雄 龚卫国 潘英俊 李伟红 刘嘉敏 张红梅 提出了一种将傅里叶变换和奇异值分解相结合的人脸自动识别方法.首先对人脸图像进行傅里叶变换,得到其具有位移不变特性的振幅谱表征.其次,从所有训练图像样本的振幅谱表征中给定标准脸并对其进行奇异值分解,求出标准特征矩阵,再将人脸的振幅谱表征投影到标准特征矩阵后得到的投影系数作为该人脸的模式特征.然后,对经典的最近邻分类器算法进行了改进,并采用模式特征之间的欧式距离作为相似性度量,从而完成对未知人脸的识别.采用ORL (Olivetti Research Laboratory)人脸库对本文提出的人脸识别方法进行验证,获得了100.00 的识别率.实验结果表明,本方法优于现有的基于奇异值分解的人脸识别方法,且对表情、姿态变换等具有一定的鲁棒性. (Face recognition based on singular value decomposition method Deliberate simultaneously Gong Weiguo Li Wei Hung Stephen Lau, Hong-Mei Zhang Ying-Jun Pan Paper, a Fourier transform and singular value decomposition of the combination of automatic face recognition. First of all, the face image by Fourier transformation, it has the same characteristics of the displacement amplitude spectra. Secondly, all training The amplitude spectrum of the sample images given in standard face representation and its singular value decomposition, find the standard characteristic matrix, then the amplitude of spectral characterization of human faces projected onto the standard characteristic matrix of projection coefficients obtained as the face of the model features . Then, the classical nearest neighbor classifier is improved, and the use of Euclidean distance between pattern features as the similarity measure, thus completing the identification of unknown human faces. using ORL (Olivetti Research La)

雷达面阵的波束形成及三维的波束指向图 Beamforming radar plane and three-dimensional array beam pointing Figure