"Individual-Driven Spiking-Mixer Deep Learning Model for IRS-Assisted ..."

Taisei Urakami et al. (2023)

> Home

Details and statistics

DOI: 10.1109/GCCE59613.2023.10315443

access: closed

type: Conference or Workshop Paper

metadata version: 2024-08-04

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/gcce/UrakamiJZCO23
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/gcce/UrakamiJZCO23
Taisei Urakami, Haohui Jia, Dafang Zhao, Na Chen, Minoru Okada:
Individual-Driven Spiking-Mixer Deep Learning Model for IRS-Assisted mmWave Systems Beam Training. GCCE 2023: 296-297

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.