Bayesian Uncertainty Modeling for P300-Based Brain-Computer Interface

Bayesian Uncertainty Modeling for P300-Based Brain-Computer Interface

P300 potential is important to cognitive neuroscience research, and has also been widely applied in brain-computer interfaces (BCIs). To detect P300, many neural network models, including convolutional neural networks (CNNs), have achieved outstanding results. However, EEG signals are usually high-d...

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Podrobná bibliografie
Hlavní autoři: Ronghua Ma, Hao Zhang, Jun Zhang, Xiaoli Zhong, Zhuliang Yu, Yuanqing Li, Tianyou Yu, Zhenghui Gu
Médium: Článek
Jazyk:English
Vydáno: IEEE 2023-01-01
Edice:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Témata:
Bayesian neural network (BNN)
brain-computer interface (BCI)
deep learning
P300
uncertainty estimation
On-line přístup:https://ieeexplore.ieee.org/document/10153625/

Internet

https://ieeexplore.ieee.org/document/10153625/

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