MATLAB-7

Matlab PNN network with realization using simple console

基于遗传算法的组卷设计，此为书籍版本。。。。(Design based on genetic algorithm test paper, this is the book version. . . .)

EM算法用于混合高斯模型的参数估计，并附有一个例子进行说明，程序解释(EM algorithm is used for of the gaussian mixture model parameter estimation, and with an example specification, process explanation)

使用matlab做关于雷达的仿真，并且含有雷达性能的讲解与代码(Use matlab to do simulations on the radar, and contains the code to explain radar performance)

MATLAB实现潮流计算的程序基本使用牛顿拉夫逊法进行计算(Matlab load flow)

说明：  用MATLAB生成bpsk信号，并通过AWGN信道的仿真(MATLAB bpsk signal generation, and through the AWGN channel simulation)

一套很好的Matlab学习教程，值得一看~~~(A good Matlab Tutorial)

室内环境的人体感应是物联网应用在安保、智能家居、节能环保方面的关键问题，近年来多普勒雷达体制的微波人体感应器作为一种高性能的室内人体传感器成为了一种热门的解决方案。微波人体感应器以雷达体制主动发射微波信号，探测回波中由目标人体产生的多普勒，输出触发信号。 国内外现有微波开关面临的主要问题是静止人体目标检测。本项目系统检测人体呼吸心跳微信息，拟通过长时间累积和滤波器提取微多普勒信息检测动目标。( Of the indoor environment of the human body induction is the Internet of things application in security, smart home, energy-saving environmental protection, the key problem of doppler radar system in recent years as a kind of high performance microwave sensor body interior human body sensor has become a popular solution. Body of microwave sensor to active microwave signal launch radar system, the detection by the target echo in the bodies of doppler, trigger signal output. Of the main problems in the domestic and foreign existing microwave switch target detection is still the human body. The project system to detect human breathing heartbeat micro information, through long time accumulation and filter extract micro-doppler information detection target. )

One dimensional problem in class (nonlinear) Geometry: A=1, uniform cross-section L=2, total length of bar BC at x=0, u=0 BC at x=L, f=3.75 Material : nonlinear elastic E=10 sigma=E*(epsilon+epsilon^3)

　计算机人脸识别技术( Face Reocgnition)就利用计算机分析人脸图像,从中提取出有效的识别信息,用来辨认身份的一门技术。[ 1 ]即对已知人脸进行标准化处理后,通过某种方法和数据库中的人脸样本进行匹配,寻找库中对应人脸及该人脸相关信息。人脸自动识别系统有两个主要技术环节,一是人脸定位,即从输入图像中找到人脸存在的位置,将人脸从背景中分割出来,二是对标准化后的人脸图像进行特征提取和识别。本文中介绍的PCA (特征脸)方法就是一种常用的人脸 特征提取方法。(Computer Face Recognition Technology (Face Reocgnition) on the use of computer analysis of facial image, to extract the valid identification information used to identify the status of a technology. [1] that is known to standardize treatment of face, through a method and a database of face samples for matching, search library, the corresponding face and the face-related information. Automatic face recognition system has two main technical aspects, first, face location, that is, from the input image to find the location of the face there, the faces will be split out from the background, the second is, the standard features of face images extraction and recognition. Described in this paper PCA (Eigenfaces) method is a common facial feature extraction method.)