Multi-person feature fusion transfer learning-based convolutional neural network for SSVEP-based collaborative BCI

Multi-person feature fusion transfer learning-based convolutional neural network for SSVEP-based collaborative BCI

ObjectiveThe conventional single-person brain–computer interface (BCI) systems have some intrinsic deficiencies such as low signal-to-noise ratio, distinct individual differences, and volatile experimental effect. To solve these problems, a centralized steady-state visually evoked potential collabor...

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Bibliographic Details
Main Authors: Penghai Li, Jianxian Su, Abdelkader Nasreddine Belkacem, Longlong Cheng, Chao Chen
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-07-01
Series:Frontiers in Neuroscience
Subjects:
steady-state visually evoked potential
collaborative BCI
feature fusion
convolutional neural network
transfer learning
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2022.971039/full

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https://www.frontiersin.org/articles/10.3389/fnins.2022.971039/full

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