ADRC-with-MATLAB-Simulation

本程序是主成分分析，可以解决几个几个输入之间的相关性，能够提取出多输入的主成分(This program is the principal component analysis can solve several several input correlation between the principal components can be extracted multiple input)

Often we are interested to see how the adaptation of the coeffi cients works or how the error behaves over time. Therefore we need the function [y,e,c]=lms2(x,d,N,mu) which provides us more output arguments

the newer version from HMMbox 3.2 Matlab toolbox for Variational estimation Hidden Markov Models. (Adapted from Hidden Markov Toolbox Version 3.3 01-Apr-99 and Coupled Hidden Markov Toolbox Version 1.1 01-Feb-01 Copyright (c) by Iead Rezek, Oxford University) The software uses some NETLAB routines (see http://neural-server.aston.ac.uk/netlab/index.html so you ll need to have NETLAB on your search path See the file VERSION for what s new in this version. The observation models has so far been implemented are Gaussian, Poisson and Dirichlet

matlab源代码，可能对研究LDPC码的同仁是有很大帮助的(matlab source code, may be the study of Tongren LDPC code is of great help)

agood book for learning fuzzy clips

说明：  该程序用全搜索法实现图像间的匹配，同时有视频foreman作为处理的考虑视频(The program uses the full search method to achieve matching between images, while there is a deal considering Video foreman video)

说明：  我的毕设源码，希望对大家有所帮助，基于Matlab环境实现(the design program for graduation)

虚拟同步机的并网simulink模型，主要是VF+DROOP CONTROL的结合，解决了虚拟阻抗的加入(Virtual machine synchronization and network simulink model is mainly a combination VF+DROOP CONTROL solve the virtual impedance added)

详细介绍matlab的许多有用的功能和一些重要功能的语法，并加一些经典试验(Matlab detail the many useful features and some important features of the grammar, and add some classical test)

2017年0616，该频域分解（FDD）土木工程中的一个输出系统识别技术的流行，特别是在结构健康监测。作为一个输出的算法，它是有用的当输入数据是未知的。FDD是模态分析技术，生成系统的实现采用了频率响应（多）输出数据参考。所附的MATLAB代码实现了这一技术的模态参数识别。为了使用此代码，处理（趋势、过滤等）时间的历史数据必须存储在一个Excel文件（数据每一频道栏目）。检查“加速度。对于时间的历史文件的一个实例xlsx”。(In 2017, 0616, frequency domain decomposition (FDD), an output system in civil engineering, was popular in identification technology, especially in structural health monitoring. As an output of the algorithm, it is useful when the input data is unknown. FDD is a modal analysis technique, and the implementation of the system adopts a frequency response (multiple) output data reference.)