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Random Fourier Feature Based Deep Learning for Wireless Communications
  • Rangeet MItra ,
  • Georges Kaddoum
Rangeet MItra
ETS Montreal

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Georges Kaddoum
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This paper provides analytical results on fixed kernel width based RFF based DL (RFF-DL). The derived analysis and the presented case-studies indicate the RFF-DL’s robustness to kernel-width initializations, and offers improved convergence in the low-data regime.
Jun 2022Published in IEEE Transactions on Cognitive Communications and Networking volume 8 issue 2 on pages 468-479. 10.1109/TCCN.2022.3164898