TD2_NL

可以供在SVM门口的初学者早日入门，这些都是最基本的SVM程序，但是也比较专业，希望有需要的人使用(SVM can be at the door for an early entry for beginners, these are the most basic SVM procedure, but more professional, I hope the person has required the use of)

阵列信号处理中DOA估计的傅氏变化算法的matlab程序(the matlab code for Fouries algorithm of DOA estimation of array signal processing)

simulation of distributed power flow controller...

小波分析理论与MATALB R2007 实现第十二章演示代码(Wavelet analysis theory and MATALB R2007 A Chapter 12 demo code)

face detetion in matlab

压缩感知目前广泛应用于雷达成像或得超分辨稀疏成像，该文件为压缩感知三维成像。(Compressed sensing has been widely applied in radar imaging or sparse super resolution imaging, the file is compressed perception three-dimensional imaging. )

此压缩包包含两个程序，一个为录音程序，另一个为放音程序，皆用MATLAB编写，可以改变采集信号的频率和指定播放频率。是在学习数字信号处理中用到的一个小练习。欢迎尝试运行，和进一步修改。(This compressed package contains two programs, one for recording the program, and the other for playback program, are using MATLAB, you can change the frequency of collection and the specified playback signal frequency. Digital signal processing is used to learn a little practice. Welcome to try to run, and further modified.)

120多个用MATLAB编写的信号处理程序，它们是本书各个章节的大部分例题。用MATLAB编写的程序的名称由“exa”开头，接下来是所在的章、节及例题的序号，如exa010101,指的是第1章第1节（即1.1节）的第1个例题，即例1.1.1。如果该程序是为了说明某一个m文件的应用，则在上述名称的后面跟一个下划线，再在后面加上所说明的MATLAB文件的名称，如exa011001_rand，即是例1.10.1,该例用来说明rand.m文件的应用。(More than 120 signal processing programs written in MATLAB are most of the examples in each chapter of this book. The name of the program written in MATLAB begins with "exa", followed by the ordinal number of the chapters, sections and examples, such as exa0101, which refers to the first example of chapter 1, section 1 (i.e. section 1.1), namely example 1.1.1. If the program is to illustrate the application of an M file, then follow the above name with an underscore, and then add the name of the MATLAB file, such as exa011001_rand, which is Example 1.10.1. This example is used to illustrate the application of rand.m file.)

distance snaked的matlab实现，用于分割和边缘检测(matlab realize the distance snaked for segmentation and edge detection)

In image processing, probably the most familiar is the image brightness and contrast adjustment