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runica
- 提出了一种利用S函数实验结果表明：ICA可以将 脑电信号中包含的心电（ECG）、眼电（EOG）等多种干扰信号成功地分离出来-use of a S-function experimental results show : ICA EEG can be included in the heart (ECG), eyes (EOG) and other interference signal successfully separated
CSPfilter
- Common spatial pattern 公共空间模式滤波是处理脑电信号的一种方法，它可以使两类想象运动EEG的协方差之间的差距最大化，便于后期的分类处理。-Common spatial pattern model of public space filtering is a method of EEG signal processing, it can make two types of movement EEG covariance imagine the gap between the
p300FeatureExtraction
- 自动提取和分类脑电EEG信号P300的特征的遗传算法-A Genetic Algorithm for Automatic Feature Extraction in P300 Detection
PhaSpaRecon
- 应用多变量相空间重构对分析脑电信号Multivariate analysis of the phase space reconstruction of the EEG-Multivariate analysis of the phase space reconstruction of the EEGMultivariate analysis of the phase space reconstruction of the EEG
EdF-read
- 快速定点独立分量分析算法编码能有效提取心电或脑电信号-Fast fixed-point independent component analysis algorithm can effectively extract the encoded ECG or EEG
FacialFeatures-EEG
- EEG classification using neural networks1
Matlabscripts_for_aam
- EEG classification using neural networks2
TBM_codes
- EEG classification using high accuracy TEA
cspnum1
- csp算法，异步脑机接口特征值提取。脑－机接口(brain-computer interface，BCI)技 术提供了一种非肌肉控制的通讯通道，使大脑可以直接和外部环境进行信息交 互。脑－机接口将人脑的信号直接转换成对外部设备的控制命令，信息的传递 不再需要经过外周神经和肌肉等传出通道[1-In motor imagery-based Brain Computer Interfaces (BCI), discriminative patterns can be extracted
2000061
- Blinking Artefact Recognition in EEG Signal Using Artificial Neural Network
biosig4octmat-2.81.tar
- 最新版的biosig4octmat程序，适用于EEG信号的特征提取和分类，以及分类器的性能评价-The the the latest version biosig4octmat program applies to EEG signal feature extraction and classification, and the performance evaluation of the classifier
EEG-hard-threshold--soft-threshold
- 脑电信号的硬阈值和软阈值去噪算法，是对脑电信号消噪的基本消噪能够成功取得脑电消噪的目的，为脑电信号的特征提取做好充分准备-EEG hard threshold and soft thresholding algorithm is the basic noise cancellation EEG de-noising can successfully achieve the purpose of de-noising EEG, EEG feature extraction is fully pre
Garrote-thresholding
- Garrote阈值对脑电信号去噪,能有效消除白噪声干扰,提取有用的脑电信号-Garrote threshold for EEG de-noising, can effectively eliminate white noise, extract useful EEG
filter
- 巴特沃斯滤波器对脑电信号进行滤波，分别对低通、中通、高通滤波器进行设计，此文件是源码和脑电数据。-Butterworth filter for filtering EEG signals were low-pass, pass, high-pass filter design, this file is the source and EEG data.
SleepWakeStaging
- 睡眠分析源程序，非常详细专业的脑电分析程序，非常适合脑电分析的学生-Sleep source analysis, very detailed professional EEG analysis program, EEG analysis is ideal for students
analysis_prog
- 用EEG数据结合机器学习算法开发人工智能工具-Combined with the EEG data machine learning algorithm development of artificial intelligence tools
基于方差和深度学习的脑电信号分类算法
- 从深度学习方面解析脑电信号，通过方差计算脑电特征(Analysis of EEG signals from deep learning and calculation of EEG characteristics by variance.)
脑电数据PCA处理及SVM分类
- 脑电eeg数据预处理，用于脑电信号的MATLAB处理程序，输入处理数据，进行matlab运算，PCA处理及SVM分类。(PCA Processing and SVM Classification of EEG Data)
cntData_CSP_FLDA
- 本算法针对运动想象的脑电数据，进行预处理并后续用分类器做分类。 该实验所用的的脑电特征提取方法主要是csp空间滤波，并后续用FLDA来进行特征分类。最终得到较好的效果(In this algorithm, the EEG data of motion imagination are preprocessed and then classified by classifier. The main feature extraction method of EEG in this experime