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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
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脑电想象运动的csp特征提取分类算法 matlab平台，通过投票可以直接扩展到多类-Imagine the movement csp EEG feature extraction classification algorithm matlab platform, through the vote can be directly extended to multiple classes
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小波神经网络用于分类的基础源码，供参考！-Wavelet neural network for classification of basic source for information!
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Matlab source for blind classification of EEG data (BCI competition II data set IV)
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基于多通道脑电特征运动意识任务的分类，-Characteristics of movement based on multi-channel EEG classification of mental tasks,
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用于脑电信号的检查和分类
高度集成化，简单容易-Used for EEG examination and classification of highly integrated, simple and easy to
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this matlab program is for EEG signal classification
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EEG signal classification by SVM
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pca分类程序，主要用于脑电信号的分类。具有较好的分类精度！-pca classification procedures, mainly for the classification of EEG signals. Has better classification accuracy!
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EEG signal classification using wavelet feature extraction
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EEG signal classification using wavelet feature extraction
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EEG signal classification using wavelet feature extraction
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EEG signal classification using wavelet feature extraction
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基于mu节律能量的140组脑电信号的决策分类，从3s到9s之间不同决策时间点的识别率，最高为85 -140 mu rhythm-based energy group decision-making EEG classification, from 3s to 9s different decision points in time between the recognition rate up to 85
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EEG classification using neural networks1
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该程序描述了SVM神经网络的数据分类脑电信号种类识别。-The program describes the SVM neural network data classification EEG species identification.
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this code reduce the dimentional of feature space using combine sparse matrix+PCA for classification eeg signal. more detail exixst inside the code.
this code tested and work properly
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Code for EEG Classification
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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)
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DEAP数据集下的情绪识别分类，包括特征提取和分类(Emotion recognition classification based on deap data set, including feature extraction and classification)
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