搜索资源列表
SVM-KM
- 一种很容易理解的svm matlab工具箱，可用于分类，回归，并附很多示例。-A very easy to understand svm matlab toolbox, can be used for classification, regression, together with many examples.
Wavenetrecogniton
- 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!
High_Accuracy_Classification_of_EEG_Signal
- 里面有了巧妙的方法提高了脑电信号分类准确性，有做EEG分类的可以看看。-There has been a clever way to improve the classification accuracy of EEG, and EEG classification can be done to see.
motorimage_Csp
- 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
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
classduotongdao
- 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,
etos-1.1.2.tar
- 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
predict2
- 利用神经网络训练，对EEG数据进行预测，还有分类-The neural network training, prediction of the EEG data, there are categories
Fisher
- 用MATLAB做的Fisher线性分类器，处理脑电信号，数据为bci竞赛数据-MATLAB to do with Fisher linear classifier, EEG signal processing, data race data for the bci
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 covarian
PCATEST
- 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!
mu-fisher
- 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
EEG-based-identification-method
- ：基于脑电信号的身份识别是通过采集试验者的脑部信号来进行身份认证。对于同一个外部刺激或者主体在思考同一个 事件的时候，不同人的大脑所产生的认知脑电信号不同。选取与运动意识想象有关的电极后，分析不同个体在特定状况下脑 电的个体差异，采用以回归系数、能量谱密度、相同步、线性复杂度多种信号处理结合方法对运动想象脑电信号进行处理来 进行特征提取。组合多元特征向量并运用多层BP 神经网络对不同个体的脑电信号进行分类，并在不同的意识想象
FCM-for-EEG
- 模糊C均值脑电分类并使用了支持向量机对比，其中支持向量机使用了三种方法参数寻优。-fuzzy C means clustering for EEG classification，and use the SVM for campare. The SVM applied three methods to find the optimal apartments.
EEG--classification
- 脑电信号的提取和特征分类还有滤波处理，适用于脑机接口技术中-EEG extraction and feature classification filtering process, applied to brain-computer interface technology
LS-SVMLab-v1.7
- 脑电睡眠分期svm分类器，可用于家庭监测人的睡眠(SVM classifier for electroencephalogram sleep staging)
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.)
matlab
- 用于脑电信号分析的matlab算法，对数据进行PCA处理及SVM分类。(The matlab algorithm for EEG signal analysis performs PCA processing and SVM classification on data.)
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)
EEG-Emotion-classification-master
- 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)