PCA

一个非常好的图像恢复的工具集，matlab编写的源代码。(A very good image restoration tools, matlab prepared source code.)

研究生课题利用simulink对运动目标进行仿真，涉及跳频信号处理调制解调混频时间控制。(Graduate program of moving targets using simulink simulation, signal processing, frequency-hopping modulation and demodulation involves mixing time control.)

This demonstration illustrates how to use the adaptive filter algorithms

使用matlab编写的瑞利信道的仿真，使用了simulink，在多普勒经典谱(Write the Rayleigh channel using matlab simulation, using simulink, in the classical Doppler spectrum)

算法部分是网上下的，因为应用不同，有所改动，界面程序是我自己加的，很简陋，但是能用，有的地方原程序被注释掉了，是为了保持原有程序的语句，怕删掉以后回不去。运行时注意地址和函数调用格式 (poor)

OMP算法的实现、测试，此外还包括相应的c/c++代码。(OMP algorithm)

数字图像滤波的程序，包括散斑噪声的生成，中值，均值，Lee，Kuan滤波算法的实现，还计算了三个指标：峰值信噪比，等效视数，散斑指数。(Digital image filtering process, including the generation of speckle noise, median, mean, Lee, Kuan filtering algorithm, also calculated three indicators: the peak signal to noise ratio, equivalent number, speckle index.)

VC MATLAB 混编示例 ppWizard has created this matlab调用 application for you. This application not only demonstrates the basics of using the Microsoft Foundation classes but is also a starting point for writing your application. This file contains a summary of what you will find in each of the files that make up your matlab调用 application.(ppWizard has created this matlab调用 application for you. This application not only demonstrates the basics of using the Microsoft Foundation classes but is also a starting point for writing your application. This file contains a summary of what you will find in each of the files that make up your matlab调用 application.)

In this paper, we show how support vector machine (SVM) can be employed as a powerful tool for $k$-nearest neighbor (kNN) classifier. A novel multi-class dimensionality reduction approach, Discriminant Analysis via Support Vectors (SVDA), is introduced by using the SVM. The kernel mapping idea is used to derive the non-linear version, Kernel Discriminant via Support Vectors (SVKD). In SVDA, only support vectors are involved to obtain the transformation matrix. Thus, the computational complexity can be greatly reduced for kernel based feature extraction. Experiments carried out on several standard databases show a clear improvement on LDA-based recognition

说明：  直扩信号BPSK的仿真，采用异或移位的算法实现PN码达到扩频的目的(BPSK DS signal simulation, using different algorithms, or shift the PN code to achieve the purpose of spreading)