HMM_network

Stateflow7 User Guide

用矩量法计算天线辐射特性的MATLAB演示程序，程序很紧凑，执行效率很高(Moment method antenna radiation characteristics of MATLAB demonstration program, the program is very compact, high efficiency in the implementation)

MathNet C# Numeric Algorithm Library

非常完美的OFDM程序，已经在MATLAB验证过，完全能用！！！(Perfect OFDM program has been validated in MATLAB, can be used completely! ! !)

蚁群算法的matlab实现程序，简单易懂，对于学习者来说，不错(Ant colony algorithm matlab implementation process, easy to understand, for a student perspective, it is true)

基本的ICA算法代码,进行有效的特征提取，是一种降维方法。(the matlab code of ICA)

Quadrocopter model in Simulink with basic PID controller

模拟分析参数的相合性:设总体服从拉普拉斯分布，用MATLAB模拟分析参数贝塔的相合性(Consistency simulation parameters: Let overall obey Laplace distribution, consistency of analysis with MATLAB simulation parameters betas)

MATLAB 课本实例教程MATLAB 课本实例教程MATLAB 课本实例教程MATLAB 课本实例教程(MATLAB)

独立成分分析（Independent Component Analysis, ICA）是近年来发展起来的一种有效的盲分离技术，最早是由法国学者Herault和Jutten于1986年提出。ICA方法的提出最初是用来解决“鸡尾酒会”问题，其过程可以归纳为，在源信号与传输通道参数均未知的情况下，仅根据源信号的统计特性，出现测信号恢复出源信号。ICA分析的关键在于根据一定的优化准则建立描述输出信号独立程度的优化判据，即目标函数，并设计相应的优化算法，寻求最优的分离矩阵，使得输出信号中各分量尽可能相互独立。采用ICA方法对信号进行盲分离时，可避免过多地受大能量噪声成分的影响，将部分小能量信号源识别出来。随着ICA技术的不断发展，目前ICA技术已经广泛应用于语音增强、音频识别、通信、医学信号处理、金融数据挖掘、图像消噪、数字水印、遥感等领域，并取得了一定的研究成果。(Independent Component Analysis (ICA) Component ini order, developed in recent years is a kind of effective separation technology, originally from French scholars Herault and Jutten in 1986. The proposed method is initially ICA to solve the "cocktail" problem, the process can be divided into, in the source signal transmission channels and in the case of unknown parameters according to the source of the signals, and the statistical characteristics of recovering the source signal. According to the analysis of the ICA key lies in the establishment of optimal criteria described the output signal of the independent, objective function optimization criterion, and the corresponding optimization algorithm, the optimum )