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 (SampE...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Published: |
2013
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84886467593&doi=10.1109%2fEMBC.2013.6610480&partnerID=40&md5=ec2884cf099e80d3f8ecef996599a54a http://eprints.utp.edu.my/32664/ |
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