Riemann-Based Algorithms Assessment for Single- and Multiple-Trial P300 Classification in Non-Optimal Environments - Université de Versailles Saint-Quentin-en-Yvelines
Journal Articles IEEE Transactions on Neural Systems and Rehabilitation Engineering Year : 2020

Riemann-Based Algorithms Assessment for Single- and Multiple-Trial P300 Classification in Non-Optimal Environments

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Human-Computer Interaction [cs.HC] Signal and Image Processing

Sylvain Chevallier  : Connect in order to contact the contributor

https://hal.uvsq.fr/hal-03174333

Submitted on : Friday, March 19, 2021-10:09:53 AM

Last modification on : Thursday, December 21, 2023-11:56:08 AM

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hal-03174333 , version 1 (19-03-2021)

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Juan Delgado, David Achanccaray, Elizabeth Villota, Sylvain Chevallier. Riemann-Based Algorithms Assessment for Single- and Multiple-Trial P300 Classification in Non-Optimal Environments. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2020, 28 (12), pp.2754-2761. ⟨10.1109/TNSRE.2020.3043418⟩. ⟨hal-03174333⟩

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UVSQ LISV UNIV-PARIS-SACLAY GS-ENGINEERING GS-COMPUTER-SCIENCE GS-SPORT-HUMAN-MOVEMENT INSTITUT-SCIENCES-LUMIERE
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