DTP-Net: Learning to Reconstruct EEG Signals in Time-Frequency Domain by Multi-scale Feature Reuse.

已完结 10 由林静发布于 2024/3/21 18:03:23

DOI:10.1109/JBHI.2024.3358917
作者：安上
文献类型：期刊论文
补充材料：只需要正文
文献链接：https://doi.org/10.1109/JBHI.2024.3358917

Institute of Electrical and Electronics Engineers (IEEE)

Abstract：Electroencephalography (EEG) signals are prone to contamination by noise, such as ocular and muscle artifacts. Minimizing these artifacts is crucial for EEG-based downstream applications lik

应助信息

求助已完结，文件已删除 如有需求请重新发布求助一键发布

感谢使用Book学术
本站所有文献仅供个人学习和参考，请勿将文件进行传播。共同遵守网站规定和相关知识产权规定。

上一个求助:其它数据库Naturally Fractured Carbonate Reservoir Characterization: A Case Study of a Mature High-Pour Point Oil Field in Hungary 下一个求助:Oxford University PressAssociation between ambient temperature exposure and pregnancy outcomes in patients undergoing in vitro fertilization in Shanghai, China: a retrospective cohort study.