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Updated: Jul 13, 2026

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

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Published on: October 24, 2012

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BA-ATEMNet:贝叶斯式学习和多头自我注意力用于空中短暂的电磁信号的理论否定

Weijie Wang1,2, Xuben Wang1, Xiaodong Yu3,4

  • 1School of Geophysics, Chengdu University of Technology, Chengdu 610059, China.

Sensors (Basel, Switzerland)
|January 11, 2025
PubMed
概括

一个新的深度学习网络,BA-ATEMNet,有效地拒绝空中的短暂电磁 (ATEM) 信号,改善矿产勘探. 这种先进的方法可以在复杂的地质环境中提高信号清晰度.

关键词:
贝叶斯式学习是贝叶斯式学习.在空中传递的短暂电磁方法.深度学习是一种深度学习.多头自我注意力机制.信号无声化 信号无声化

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