invariance

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

本书系统介绍MATLAB遗传算法和直接搜索工具箱的功能特点、编程原理及使用方法。(This book systematically introduce MATLAB Genetic Algorithm and Direct Search Toolbox features, programming principles and use.)

谱分析的源程序，适合通信等专业的初学者学习使用，希望给需要的人帮助(Spectral analysis of the source, suitable for beginners to learn communication and other professional use, I hope to those who need help)

MATLAB SIMULINK建模与仿真实例精讲_程序(MATLAB SIMULINK)

这个一个通过matlab实现的一个日历显示程序，读取本地日历，界面很好看，程序设计的很精炼。(This is a matlab implementation of a calendar display program, read the local calendar interface look very good program design is very refined.)

sinc插值函数，在SAR、ISAR，通信等信号处理中有广泛的应用，是非常好的学习代码。(sinc interpolation function, there is a wide range of applications in the SAR, ISAR, communications and other signal processing, is a very good learning code.)

此例可采用BP神经网络算法用于设备故障类型的模式识别程序。 本次为变压器故障（均为低压测故障）类型的识别。(This example can be used BP neural network algorithm for pattern recognition procedures for equipment fault type. The identification of the type of transformer fault (both low pressure fault detection).)

说明：  dMC动态矩阵控制单变量的，可以很容易修改成需要的相应程序。(DMC Dynamic Matrix Control of a single variable, can be easily modified to the needs of the corresponding procedures.)

matlab GUI 学习资料，里面的东西很基础，且包含一些例子(matlab GUI learning materials, which are the basis of things, and contains some examples)

spectrogram generation and using matlab for students and new learners and understanding of spectrogram concept