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| 基于小波变换的脑电信号特征提取及分类 | |
| 引用本文： | 余琴,张旭秀. 基于小波变换的脑电信号特征提取及分类[J]. 大连铁道学院学报, 2009, 0(1): 69-72 |
| 作者姓名： | 余琴 张旭秀 |
| 作者单位： | 大连交通大学电气信息学院; |
| 基金项目： | 国家自然科学基金资助项目(3050475,60372081) |
| 摘 要： | 在脑机接口中，基于小波变换法和AR模型法结合线性判别准则对两类思维任务进行特征提取及分类，提出以小波系数均值经K-L变换作为特征，用Fisher判别准则进行分类。结果表明，这种方法可以利用少量的数据提取脑电信号的特征，具有比较好的分类效果。 |
| 关 键 词： | 脑机接口 小波变换 特征提取 线性判别 |
EEG Feature Extraction and Classification in Brain Computer Interface Based on Wavelet Transform |
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| YU Qin,ZHANG Xu-xiu. EEG Feature Extraction and Classification in Brain Computer Interface Based on Wavelet Transform[J]. Journal of Dalian Railway Institute, 2009, 0(1): 69-72 | |
| Authors: | YU Qin ZHANG Xu-xiu |
| Affiliation: | YU Qin,ZHANG Xu-xiu(School of Electrical & Information Engineering,Dalian Jiaotong University,Dalian 116028,China) |
| Abstract: | In brain-computer interface(BCI),feature extraction and classification of two types of thinking tasks are conducted based on wavelet transform and AR model combined with linear criteria.The feature can be expressed by mean wavelet coefficient converted by K-L transformation,and the classification can be made by Fisher criteria.The results show that the method can extract features using less data with higher classification performance. |
| Keywords: | brain-bomputer interface(BCI) wavelet transform feature extraction linear criteria |
| 本文献已被 CNKI 维普 等数据库收录！ | |