MATLABAndItsApplicationInPowerSystemSimulationStud

本文件是关于阵列天线方面的方向图计算程序(This document is on aspects of array antenna pattern calculation program)

这里面有5个程序，一是sarima预测的，2是HHT变换计算的主程序，3是计算平均周期的，4是人工神经网络的主程序，5是计算lyapunuv数字的主程序，计算域与eemd分解有关的股市预测方面的主程序(farcast mainprogram)

我们将五个连续时间信号转换成离散时间信号(we change five continuous signals into discrete signal. )

Sorting, Searching, and Classification using 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 )

一种高效快速的线性混合新河盲分离ICA算法，提供了6个源信号以供参考，分离效果很好(An efficient linear mixed fast ICA algorithm for blind source separation New River, providing 6 source signal for reference, a good separation effect)

2010 数学建模大赛 赛前matlab培训4(MATLAB programming topics lecture 4.zip)

power_sfavg.rar,功率电子领域matlab仿真文件，已经验证过，程序运行正常(power_sfavg.rar, ,Power electronics field matlab simulation file, has already been verified, the normal operating procedures)

心电数据的匹配，hilbert变换用于心电的检测和分析 (ECG data matching, hilbert transform ECG for the detection and analysis)

you should use matlab csma