EEG Classification of Physiological Conditions in 2D/3D Environments Using Neural Network
Higher classification accuracy is more desirable for brain computer interface (BCI) applications. The accuracy can be achieved by appropriate selection of relevant features. In this paper a new scheme is proposed based on six different nonlinear features. These features include Sample entropy (Samp...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://eprints.utp.edu.my/10914/1/11870472.pdf http://embc2013.embs.org/ http://eprints.utp.edu.my/10914/ |
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