Channel selection by Rayleigh coefficient maximization based genetic algorithm for classifying single-trial motor imagery EEG
文献类型：期刊论文
| 作者 | He, Lin; Hu, Youpan; Li, Yuanqing; Li, Daoli |
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2013 |
| 英文摘要 | While common spatial pattern may be the most widely used feature for discriminating motor imagery based EEG signals, Rayleigh coefficient maximizationenable us to have one more effective. However, such a feature is often deteriorated by redundant electrode channels which may result in low classification accuracy, extra subsequent computational load and difficulty in understanding which part of the brain relates to classification-relevant activity. In this paper, we present a channel selection method to deal with these problems, in which an improved genetic algorithm based on the Rayleigh coefficient feature is conducted to determine the optimal subset of channels. Experiment results on two motor imagery EEG datasets verify that our method is effective in channel selection forclassifying motor imagery EEG signals. (C) 2013 Elsevier B.V. All rights reserved. |
| 收录类别 | SCI |
| 原文出处 | http://www.sciencedirect.com/science/article/pii/S0925231213005171 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/5278]  |
| 专题 | 深圳先进技术研究院_南沙所 |
| 作者单位 | NEUROCOMPUTING |
| 推荐引用方式 GB/T 7714 | He, Lin,Hu, Youpan,Li, Yuanqing,et al. Channel selection by Rayleigh coefficient maximization based genetic algorithm for classifying single-trial motor imagery EEG[J]. NEUROCOMPUTING,2013. |
| APA | He, Lin,Hu, Youpan,Li, Yuanqing,&Li, Daoli.(2013).Channel selection by Rayleigh coefficient maximization based genetic algorithm for classifying single-trial motor imagery EEG.NEUROCOMPUTING. |
| MLA | He, Lin,et al."Channel selection by Rayleigh coefficient maximization based genetic algorithm for classifying single-trial motor imagery EEG".NEUROCOMPUTING (2013). |
入库方式： OAI收割
来源：深圳先进技术研究院
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