摘要
在脑-机接口的研究中分类识别技术占有重要地位。介绍了一种方法,用于对单次信号的分类。这种方法主要思想是将共空域子空间分解和支持向量机相结合,以便提取信号特征。该方法被用于"BCICompetition2003"第IV数据包上,分类正确率达89%。
Identification and classification technology plays an important part in study of the BCI system.Presents an algorithm for classifying single-trial electroellcephalogram( EEG).It combines common spatial subspace decomposition with support vector machine to extract features from multichaunel EEG.This algorithm is applied to the data set IV of "BCI Competition 2003" with a classification accuracy of 89% on the test set.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第34期204-206,232,共4页
Computer Engineering and Applications
关键词
脑电信号
脑-机接口
支持向量机
共空域子空间分解
electroencephalogram
Brain-Computer Interface(BCI)
Support Vector Machine(SVM)
Common Spatial Subspace Decomposition(CSSD)