单元平均恒虚警检测

说明：  matrix converter with induction motor

说明：  matlab的GUI设计，实现摄像头的无人监控拍照，可以实现定时功能。(matlab GUI design, implementation, unmanned surveillance camera pictures, you can achieve timing.)

本文从理论上对LFM-CW 雷达进行了信号分析，并对LFM-CW 雷达的信号 处理方法进行了简单研究，最后通过仿真程序验证了该信号处理方法（距离/多普勒处理） 在计算运动目标距离和速度时的正确性，为LFM-CW 雷达信号处理提供了理论依据。(This paper analyze the signal of LFM-CW radar by theory, and research the signal process method of LFM-CW radar. In the end, this paper validate the signal process method’s correctness to calculate the moving target’s distance and speed by emulate program. This paper offer the theory for the signal process method of LFM-CW radar.)

在此项目中，我们使用图像背景减法运动检测，然后我们利用卡尔曼滤波跟踪检测 object.kalman 筛选器是不同的 baysiyem filter.in 我们认为这个项目 guasian。

matlab的有限元计算代码，可计算梁、桁架等结构(matlab，FEM)

说明：  page变换例程，可以对信号进行柯恩类时频分布中的page变换(page conversion routines, you can type on the signal time-frequency distribution of Cohen)

对答题卡考生考号进行识别，对图片进行灰度，切割处理，其中有部分实用对网站的建设。(Candidate number on the answer sheet to identify candidates, on the image to gray scale, cut processing, in which some practical construction of the site.)

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)

对于智能天线的设计仿真 包含有详细的说明(for smart antenna design simulation contains detailed explanation)

matlab实现人脸库图像的剪裁,包括剪裁以及图像的旋转(Matlab achieve the cut of the face database images.)