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Updated: May 17, 2026

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EMPT:用于基于EEG的运动图像识别的稀疏性变压器

Ming Liu1, Yanbing Liu1, Weiyou Shi1

  • 1International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong, China.

Frontiers in neuroscience
|May 9, 2024
PubMed
概括

这项研究引入了一种新的深度学习模型,即EMPT,用于解码脊髓损伤患者的脑电图 (EEG) 信号,这些患者接受运动图像任务. 通过结合专家混合和ProbSparse自我注意力,EMPT实现了高精度,使EEG分析更有效.

关键词:
专家的混合 专家的混合变压器 变压器 变压器深度学习是一种深度学习.运动图像图像学自己注意力自我注意力

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