Sand2D_CA

本文在Matlab7．5下面实现了fisherface算法，选用的人脸库是ORL，其中有40 人，每人有10幅不同的人脸图像。本文选取了每人9幅作为训练(1幅作为测 试)，图像大小为112x92。(In this paper, the following Matlab7.5 realized fisherface algorithm, selection of face database is ORL, in which 40 people, each person will have 10 different people face image. This article is selected as a training per nine (one as a test), image size is 112x92.)

matlab非平稳信号噪声消除 小波变换与傅里叶变换对比(matlab noise elimination of non-stationary signal Wavelet Transform and Fourier Transform Comparison)

c means functionality

说明：  基于m序列的直接序列扩频系统的抗噪声性能仿真 (Anti-noise performance simulation based on direct sequence spread spectrum system m sequences)

利用matlab控制3维仿真软件sonnet的工具箱，里面包含了详细的试用说明PDF，还有一个微带天线的例子，使得对天线的设计变得简单。(Using matlab to control 3-D simulation software sonnet Toolbox, which contains a detailed description of the trial PDF, there is a microstrip antenna example, makes the simple antenna design.)

现需要在高度为600~700KM范围内，回归周期为30天的太阳同步轨道上布置一颗L波段的合成孔径雷达卫星。 1. 请设计合适的轨道参数，并仿真对应轨道下一个运行周期内星下点轨迹图（纬度和经度两个图）； 2. 计算多普勒中心频率，多普勒调频率与纬度的关系图（设姿态角为0°，天线视角20°~60°，推荐35°）； 3. 按高斯投影方式，将星下点轨迹图投影到地图坐标上。(Now requires a height of 600 ~ 700KM range, return period of 30 days are arranged on a sun-synchronous orbit L-band Synthetic Aperture Radar satellites. 1 Please design the appropriate orbital parameters and simulate the corresponding orbit within the next operating cycle nadir trajectories (latitude and longitude two graphs) 2. Calculate the Doppler center frequency, Doppler frequency and the relationship between latitude Figure (set attitude angle is 0, the antenna angle of 20 to 60, recommended 35) 3 Press Gauss projection, the nadir trajectories projected onto the map coordinates.)

calculate the theoretical exact(in AWGN) SYMBOL ERROR RATE(Ps_SER) verses Eb/No for even numbers of bits per symbol in qam modulation

简单的数字图像处理程序，对新手很有帮助，内含很多简易程序(Digital image processing procedures)

Karhunen Loeve算法实现过程，该项算法可用于图像的压缩和分类(Karhunen Loeve algorithm process, the algorithm can be used for image compression and classification)

This file takes cropped yale face images file as input and performs classifications based on 1. Correlation 2. Eigen vector based classification (Eigen Face) 3. Fisher Linear Discriminator (FLD) (Fisher Face) The zip contains two files readyaledata.m to read the image database EigenFace-FisherFace.m to do classification as described above