DHCT-GAN: Improving EEG Signal Quality with a Dual-Branch Hybrid CNN–Transformer Network

DHCT-GAN: Improving EEG Signal Quality with a Dual-Branch Hybrid CNN–Transformer Network

Electroencephalogram (EEG) signals are important bioelectrical signals widely used in brain activity studies, cognitive mechanism research, and the diagnosis and treatment of neurological disorders. However, EEG signals are often influenced by various physiological artifacts, which can significantly...

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Bibliographic Details
Main Authors: Yinan Cai, Zhao Meng, Dian Huang
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Sensors
Subjects:
electroencephalogram (EEG)
transformer
generative adversarial network (GAN)
denoising
Online Access:https://www.mdpi.com/1424-8220/25/1/231
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