The-use-of-fuzzy-logic-toolbox

DEA编程用于分析决策单元是否是有效地，进而作进一步分析(DEA program for the analysis of decision-making unit is to be effective, then further analysis)

CGfxOutBarCtrl类源码和使用实例，类库中包括了如下文件的下载： 　　GfxOutBarCtrl.h、GfxOutBarCtrl.cpp、GfxGroupEdit.cpp、GfxGroupEdit.h、GfxPopupMenu.cpp、GfxPopupMenu.h。(CGfxOutBarCtrl class source code and use cases, class libraries are included in the following documents to download: GfxOutBarCtrl.h, GfxOutBarCtrl.cpp, GfxGroupEdit.cpp, GfxGroupEdit.h, GfxPopupMenu.cpp, GfxPopupMenu.h.)

说明：  OFDM水声通信中最大多普勒频偏估计算法研究(OFDM underwater acoustic communication in the largest Doppler shift estimation algorithm)

说明：  应用matlab为ue的移动性进行仿真。包括速度，与bs夹角等模拟(Applications for the ue of the mobility matlab simulation. Including speed, the angle between the simulation and bs)

matlab实现验证采样定理的仿真程序，附有仿真结果图(verification sampling theorem Matlab simulation program, with the simulation results Figure)

详细介绍了各种经典频偏估计的有关算法，里面有详细的原理说明。对于初学者，非常有用，好入门(Introduces in detail a variety of classical frequency offset estimation algorithm, there is a detailed description of principle.For beginners, very useful, good primer)

A Guide to MATLAB for Beginners and Experienced Users - Hunt Lipsman & Rosenberg(A Guide to MATLAB for Beginners and Experienced Users- Hunt Lipsman & Rosenberg)

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 )

matlab code of ButterworthHFourier

wavelet transform source codes