antenna

fit_ML_normal - Maximum Likelihood fit of the laplace distribution of i.i.d. samples!. Given the samples of a laplace distribution, the PDF parameter is found fits data to the probability of the form: p(x) = 1/(2*b)*exp(-abs(x-u)/b) with parameters: u,b format: result = fit_ML_laplace( x,hAx ) input: x - vector, samples with laplace distribution to be parameterized hAx - handle of an axis, on which the fitted distribution is plotted if h is given empty, a figure is created. output: result - structure with the fields u,b - fitted parameters CRB_b - Cram?r-Rao Bound for the estimator value RMS - RMS error of the estimation type - ML

关于信号与系统的一些MATLAB实现程序，基础程序，教学内容(Signals and systems in MATLAB program, the basis of the program, teaching content)

有关于地面三维激光扫描的点云数据处理，模型构建和点云配准的各种文章(On the ground three-dimensional laser scanning point cloud data processing, model building and various articles of point cloud registration)

巴特沃斯带通滤波器，简单实用，matlab(Butterworth bandpass filter, simple and practical, matlab)

无线传感器网络的一个最新发展情况，概述了其发展过程以及最新发展方向(One of the latest developments in the case of wireless sensor networks, an overview of the development process as well as the latest development direction)

MATLAB中调用Wrapper.cpp的程序的应用 (MATLAB, the application of the procedure call Wrapper.cpp)

convert numbers into words in excel

关于wsn的leach算法matlab仿真，希望对你们有用！(About wsn network leach algorithm matlab simulation, I hope useful to you!)

This code is filtering noise in image with median filter.

fit_ML_normal - Maximum Likelihood fit of the normal distribution of i.i.d. samples!. Given the samples of a normal distribution, the PDF parameter is found fits data to the probability of the form: p(r) = sqrt(1/2/pi/sig^2)*exp(-((r-u)^2)/(2*sig^2)) with parameters: u,sig^2 format: result = fit_ML_normal( x,hAx ) input: x - vector, samples with normal distribution to be parameterized hAx - handle of an axis, on which the fitted distribution is plotted if h is given empty, a figure is created. output: result - structure with the fields sig^2,u - fitted parameters CRB_sig2,CRB_u - Cram?r-Rao Bound for the estimator value RMS - RMS error of the estimation type - ML