chapter4

很经典的教材，可以看看，不过最好还是稍微有点基础，里面有些写得比较简单(chinese book for matlab primers)

说明：  灰色预测MATLAB源代码,很有用的哦.(Gray prediction MATLAB source code, very useful Oh.)

数字图像处理MATLAB演示程序。包含图像灰度处理、平滑、锐化、压缩等。运行demo.m执行主界面。(Digital Image Processing MATLAB demonstration program. Contains the image gray scale processing, smoothing, sharpening, compression. The run demo.m perform the main interface.)

Code about the speech processing for pitch enhancement

MATLAB CODE FOR DIGITAL COMMUNICATION

矢量控制方法在matlab/simulink中的仿真模型。详细且基础，有助于新手学习。(Vector control method in matlab/simulink the simulation model. Detailed and foundation to help novices learn.)

matlab 的EOF 和REOF、CCA、SVD方法(EOF and REOF CCA SVD matlab code)

根据有无固定基础设施，无线局域网又可分为BSS (Basic Service Set)和IBSS (Independent Basic Service Set)。我们要研究的ad hoc网络属于后者。假设在一个ad hoc网络中，移动节点的发射功率PTx总是恒定的。要发送数据的移动节点总是先监听信道，测量接收到的信号功率X，其中X= I + N, I为接收到的干扰，N是噪声。移动节点只有在X＜INThre时，才可以发射。式中，INThre为背景噪声门限。 在仿真中，我们规定每个移动节点的发射功率是常数，PTx = 1W；接收节点接收机的灵敏度Smin = -80 dBm；信号质量 min = 2 dB；系统的背景噪声门限INThre = 1.2e-10。 (According to the availability of fixed infrastructure, wireless local area network can be divided into BSS (Basic Service Set) and IBSS (Independent Basic Service Set). We have to study the ad hoc network belong to the latter. Assuming in an ad hoc network, mobile node s transmission power is always constant PTX. To send data to the mobile node always monitor channel, measuring the received signal power X, which X = I+ N, I was received interference, N is the noise. Mobile node only when X <INThre when it is fired. Where, INThre threshold for background noise. In the simulation, we require that each mobile node s transmission power is constant, PTx = 1W receiver node receiver sensitivity Smin =-80 dBm signal quality )

Calculate the coefficent of a plane that fits better N 3d pints

卡尔曼滤波是现代数字信号处理经典算法，本程序应用matlab语言实现利用卡尔曼滤波器跟踪机动目标。(Kalman filtering is a classic of modern digital signal processing algorithms, the application of this procedure using matlab language maneuvering target tracking Kalman filter.)