A New Method to Improve the Performance of Deep Neural Networks in Detecting P300 Signals: Optimizing Curvature of Error Surface Using Genetic Algorithm
Background: Deep neural networks have been widely used in detection of P300 signal in Brain Machine Interface (BMI) systems which are rely on Event-Related Potentials (ERPs) (i.e. P300 signals). Such networks have high curvature variation in their error surface hampering their favorable performance....
Main Authors: | Seyed Vahab Shojaedini, Sajedeh Morabbi, Mohamad Reza Keyvanpour |
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Format: | Article |
Language: | English |
Published: |
Shiraz University of Medical Sciences
2021-06-01
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Series: | Journal of Biomedical Physics and Engineering |
Subjects: | |
Online Access: | https://jbpe.sums.ac.ir/article_46648_a8618f43e79f951f39f06d269363997d.pdf |
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