A transformer-based deep neural network model for SSVEP classification

• المؤلفون الرئيسيون: Chen, Jianbo, Zhang, Yangsong, Pan, Yudong, Xu, Peng, Guan, Cuntai
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2023
• الموضوعات: Engineering::Computer science and engineering; Brain–Computer Interface; Steady-State Visual Evoked Potential
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/172792

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...