Stdp-based adaptive graph convolutional networks for automatic sleep staging

HIGHLIGHTS

• who: Yuan Zhao from the Fudan University, China have published the Article: STDP-based adaptive graph convolutional networks for automatic sleep staging, in the Journal: (JOURNAL)
• what: The authors propose an adaptive GCN based on SpikeTiming-Dependent Plasticity, named STDP-GCN. The aim of adaptive STDP graph learning is to learn graph structures using STDP. Based on the AASM standard (Berry et_al, 2012), both fully awake and drowsiness are included in the Wake stage, and the electrophysiological signals and psychological characteristics of drowsiness even continue to the N1 stage, which could be the main reason . . .
  

   

  

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