Adaptive-signal-processing

I,Q通道的 噪声过程是高斯的的,而且是互不相关的,他的功率谱也是白的. 因为I和Q通道的噪声过程是高斯的,而且是互不相关的 我们可以得到他们是相互独立(Papoulis,1984). 最后,由于I和Q通道是独立的零均值高斯过程,因此可以推导出:复信号:I+jQ,幅度是瑞丽分布的,幅度的平放是指数分布的,相位角arctan(Q/I)是在(0,2π]上均匀分布(I Q Gaussian noise)

最小生成树遍历反面的matlab代码，可以参考的，如果需要的话，可以下载啦(Minimum spanning tree traversal negative matlab code, you can refer to, if necessary, you can download it)

说明：  支持向量机（Support Vector Machine, SVM）是一类按监督学习（supervised learning）方式对数据进行二元分类的广义线性分类器（generalized linear classifier），其决策边界是对学习样本求解的最大边距超平面（maximum-margin hyperplane）(Support Vector Machine, SVM)

基于Meanshift运动目标跟踪程序，matlab写的，绝对可以运行(Moving target tracking procedures can run)

paper about A statistical analysis of wind power density based on the Weibull and Rayleigh models at the southern region of Turkey

kalman滤波，李国强，用于模态识别，先生称响应在用相应识别系统参数(kalman filtering, Li Guoqiang, for modal identification, sir, said in response to the recognition system with the corresponding parameters)

这个matlab程序实现了将一个数组变量写入一个txt文件的过程。每个数组元素占据一行。(This file writes a array into a .txt file. Each member in array occupies a line in .txt file.)

下面是我编的一个软硬阈值去噪的matlab程序 下面是我编的一个软硬阈值去噪的matlab程序：thr=sigma*(2*lgN)1/2/lg(j+1) 用[x,xn]=wnoise(2,10,6) 产生噪声测试数据-The following is Part I of a of hard and soft threshold denoising matlab procedure is the following hardware and software, I made a threshold denoising matlab program: thr = sigma* (2* lgN) 1/2/lg (j+1) by [x, xn] = wnoise (2,10,6) noise test data(thr=sigma*(2*lgN)1/2/lg(j+1) 用[x,xn]=wnoise(2,10,6) 产生噪声测试数据-The following is Part I of a of hard and soft threshold denoising matlab procedure is the following hardware and software, I made a threshold denoising matlab program: thr = sigma* (2* lgN) 1/2/lg (j+1) by [x, xn] = wnoise (2,10,6) noise test data)

现代通信系统（matlab版）（第二版）配套源代码 John G. Proakis等著 刘树棠 译 电子工业出版社出版(modern communication system (Matlab version) (2nd Edition) source code supporting John G. Proak Liushutang is waiting for the translation of the electronics industry published)

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