A transformer-based deep neural network model for SSVEP classification

A transformer-based deep neural network model for SSVEP classification

Steady-state visual evoked potential (SSVEP) is one of the most commonly used control signals in the brain-computer interface (BCI) systems. However, the conventional spatial filtering methods for SSVEP classification highly depend on the subject-specific calibration data. The need for the methods t...

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Bibliographic Details
Main Authors: Chen, Jianbo, Zhang, Yangsong, Pan, Yudong, Xu, Peng, Guan, Cuntai
Other Authors: School of Computer Science and Engineering
Format: Journal Article
Language:English
Published: 2023
Subjects:
Engineering::Computer science and engineering
Brain–Computer Interface
Steady-State Visual Evoked Potential
Online Access:https://hdl.handle.net/10356/172792

Internet

https://hdl.handle.net/10356/172792

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