yichuan

本代码为牛顿下山法求解非线性方程组。其调用格式为[r,m]=mulDNewton(F,x0,eps) 其中F:非线性方程组，x0：初始解，eps：解的精度；r：求得的一组解，n：迭代步数。(The code for Newton' s method for solving nonlinear equations. Its call format [r, m] = mulDNewton (F, x0, eps) where F: non-linear equations, x0: initial solution, eps: solution accuracy r: obtain a set of solution, n : the number of iterative steps.)

信噪比信噪比信噪比信噪比比信噪比比信噪比(snrsnrsnrsnr)

Chebfun找到一个类似的问题已经解决了别人使用作为一个模板。这一页将你们连接到几十个这样的模板,称为Chebfun例子。每一个例子是一个M-file生产文本和/或图形输出,执行,在大多数情况下,在少于5秒。你也可以执行的例子,用Matlab命令的出版得到一个包含更多的信息的故事。一类开路(出版(“文件名”))去看在你的屏幕上最快的版本或出版(“文件名”)为一个更好的格式化乳胶版本,它将出现在一个目录叫做html。公布的产量也可直接下载作为一个pdf档案。(The quickest way to solve your problem with Chebfun may be to find a similar problem someone else has solved to use as a template. This page connects you to dozens of such templates, called Chebfun Examples. Each example is an M-file producing text and/or graphical output which executes, in most cases, in less than 5 seconds. You can also execute the example with Matlab s PUBLISH command to get a more informative story. Type open(publish( filename )) to see the quickest version on your screen or publish( filename , latex ) for a better formatted LaTeX version, which will appear in a directory called html. The published output is also available for direct download as a pdf file.)

基于Capon算法的空时处理自适应算法，适用初学者(space-time adaptive beamformin based on capon)

LDA 人脸识别的 程序段 大家下着看看吧 对大家有帮助的(LDA face recognition under the program segment we take a look at the bar for all of us help)

说明：  一种基于信号二阶统计量的盲源分离方法，SOBI方法，二阶盲辨识方法(SOBI)

matlab编写的生源定位程序 采用十字阵型(matlab prepared students locate the program using cross formation)

模拟了电法测井中双感应测井在地层中的电导率相应特征(we simulate the response conductivity in formation of dual-induction logging. )

通过计算垂直缆地震产生各种波的时距曲线公式，画出其波形(By calculating Time-distance curve equation of various waveforms produced by vertical earthquakes，and draw them with matlab )

液压泵振动信号的小波包分解以及功率谱分析，仿真信号的Hilbert谱以及边际谱；仿真信号的小波包能量计算(wavelet packet decomposition and power spectrum of vibration signals for piston pump Hilbert spectrum and marginal spectrum of stimulated signals)