EEG Conformer: Convolutional Transformer for EEG Decoding and Visualization

EEG Conformer: Convolutional Transformer for EEG Decoding and Visualization

Due to the limited perceptual field, convolutional neural networks (CNN) only extract local temporal features and may fail to capture long-term dependencies for EEG decoding. In this paper, we propose a compact Convolutional Transformer, named EEG Conformer, to encapsulate local and global features...

Full description

Bibliographic Details
Main Authors: Yonghao Song, Qingqing Zheng, Bingchuan Liu, Xiaorong Gao
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Subjects:
EEG classification
self-attention
transformer
brain-computer interface (BCI)
motor imagery
Online Access:https://ieeexplore.ieee.org/document/9991178/

Similar Items

Similar Items