Lead federated neuromorphic learning for wireless edge artificial intelligence

HIGHLIGHTS

  • who: Helin Yang from the (UNIVERSITY) have published the Article: Lead federated neuromorphic learning for wireless edge artificial intelligence, in the Journal: (JOURNAL) of 17/01/2022
  • what: The authors propose lead federated neuromorphic learning (LFNL), a decentralized brain-inspired computing method based on SNNs, enabling multiple edge devices to collaboratively train a global neuromorphic model without a fixed central coordinator. The aim of the leader is to aggregate the uploaded local neuromorphic model parameters (w2, w3, u2026, wK ) from the followers. The aim of the federated learning task is to find an optimal model . . .

     

    Logo ScioWire Beta black

    If you want to have access to all the content you need to log in!

    Thanks :)

    If you don't have an account, you can create one here.

     

Scroll to Top

Add A Knowledge Base Question !

+ = Verify Human or Spambot ?