1-DFDTDcode

vivid insight into the thory of surveying and its applications by A M Chandra

关于线性调频信号的时频计算，包括了AF,WVD,重排谱图~(The traditional method of linear frequency modulation signal frequency estimation)

參考某論文發表中，使用Matlab撰寫的EZW壓縮程式碼，有些許bug無法找出，還請各位高手多多指教。(EZW compression using Matlab code written)

迫零均衡标准算法 matlab仿真 用以消除多径引起的ISI (zero_forcing EQUALIZATION with matlab)

本程序是MATLAB里关于风机的一个工具箱，方便大家对风机的研究，大家可以网上搜索相应的help文档，方便使用( This program is a fan of the toolbox in MATLAB, to facilitate the fan research, you can search online for the corresponding help document, easy to use)

实现定时控制，非常实用，可以直接调用，有需要的可以下载(Achieve timing control, very practical, you can directly call the need to be downloaded)

This is the second part of special handling, that makes PTRACE_LDT possible to implement.

FDTD仿真喇叭天线，能观察得到其电场在自由空间随时间的分布情况。(FDTD method is a time domain analysis.Here we first we design a wave-guide and there after we just increase its broad side.Our aim is to this simulation is plotting its electric field response with time and how will it response in outside free space. Here we just take 170 time steps one who can interested in antenna designing they can also plot the radiation pattern of this HORN antenna.Just take the field in the outside the mouth of HORN antenna and there do the simple formula to near filed far field transfer and measure it at your band of antenna.Best of LUCK all of you.)

人工蜂群算法改进源程序,它不同于一般的蜂群算法，收敛更快(Artificial bee colony algorithm to improve the source code, which is different the general colony algorithm converges faster)

说明：  DEAP 数据库 EEG_feature.txt 包含了1216个脑电信号样本的160维特征，每行为一个样本，每列为一种特征。特征从左至右分别是每个脑电电极的theta（1-32列）、slow alpha（33-64列）、alpha（65-96列）、beta（1-97128列）、gamma（129-160列）波段的脑电特征。 subject_video.txt 包含了1216个脑电信号对应的32名被试和38段视频信息，其中包含两列。第一列是对应的被试编号，第二列是对应的视频编号。 EEG_feature.txt 与 subject_video.txt和valence_arousal_label.txt中每行都是一一对应的，例如subject_video.txt的第二行就是EEG_feature.txt中第二个样本（第二行）的被试和视频信息；valence_arousal_label.txt的第二行也是EEG_feature.txt中第二个样本（第二行）的愉悦度和唤醒度标签。valence_arousal_label.txt中第一列为愉悦度标签，1代表positive，2代表negative；第二列为唤醒度标签，1代表high，2代表low。 DEAP数据库并未提供情感类别标签。(EEG dataset, including DEAP database and MAHNOB-HCI database)