Hollowtube

This is attitude control system software

matlab实现的最小二乘法拟合程序，其中包含了数值结果分析过程。(matlab implementation of least-squares fitting program, which includes the analysis of the numerical results.)

matlab图像处理，matlab图形识别匹配应用程序源码(matlab image processing, matlab matching pattern recognition application source code)

在DCT域，利用8*8分块DM方法，嵌入隐藏信息。可设置量化步长、选择各种经典的攻击方式和控制攻击强弱。返回误码率和峰值信噪比。利用Matlab编写。(In the DCT domain, the use of 8* 8 block DM methods, embedding hidden information. Quantization step size can be set to choose a variety of classic attacks and control the strength of the attack. Return to the bit error rate and peak signal to noise ratio. Prepared using Matlab.)

THIS FOLDER CONTAINS THE MATLAB PROGRAMS FOR CHAPTER 6 OF RADAR SYSTEMS BY MAHAFZA

该书籍详细介绍了matlab仿真的具体实现方法，对初学者掌握仿真技能十分有利。(The book details the specific method matlab simulation, simulation for beginners to master the skills are very favorable.)

图创建一个放大框，当一个按钮被按下时，根据鼠标的位置。按“+”/“ - ”，而按下按钮来增加/减少放大。按 > / < ，而按下按钮来增加/减少箱尺寸。 按住Ctrl键的同时单击离开放大图。(Figure creates a magnification box when under the mouse position when a button is pressed. Press + / - while button pressed to increase/decrease magnification. Press > / < while button pressed to increase/decrease box size. Hold Ctrl while clicking to leave magnification on figure.)

使代码框文字可以中文高亮，达到方便阅读功能(Chinese characters can make the code box highlighted, to facilitate the reading function)

用matlab来生成全息图的一个样例程序。简单实用(Using matlab to generate a sample program hologram. Simple and practical)

fit_ML_normal - Maximum Likelihood fit of the log-normal distribution of i.i.d. samples!. Given the samples of a log-normal distribution, the PDF parameter is found fits data to the probability of the form: p(x) = sqrt(1/(2*pi))/(s*x)*exp(- (log(x-m)^2)/(2*s^2)) with parameters: m,s format: result = fit_ML_log_normal( x,hAx ) input: x - vector, samples with log-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 m,s - fitted parameters CRB_m,CRB_s - Cram?r-Rao Bound for the estimator value RMS - RMS error of the estimation type - ML