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Volume 299 - The 7th International Conference on Computer Engineering and Networks (CENet2017) - Session I - Machine Learning
Analyze EEG Signals with Convolutional Neural Network Based on Power Spectrum Feature Selection
H. Jiang,* W. Liu, Y. Lu
*corresponding author
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Pre-published on: 2017-07-17 11:56:25
Published on: 2017-09-06 14:01:04
Abstract
Brain Computer Interface refers to the establishment of direct communication and control
channels between human brain and computer. The essential part of the BCI system is the
feature extraction and classification. In this paper, we proposed an improveed architecture based
on power spectrum and CNN. Furthermore, two methods of power spectrum feature extraction
are discussed. The research result shows that this system can effectively identify the left-right
brain signals and have higher classification accuracy with it reaching 82%
Open Access
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