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Hardware Realization of Nonlinear Activation Functions for NN-based Optical Equalizers

Machine Learning 2023-05-17 v1 Optics
Authors: Sasipim Srivallapanondh , Pedro J. Freire , Antonio Napoli , Sergei K. Turitsyn , Jaroslaw E. Prilepsky
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Abstract

To reduce the complexity of the hardware implementation of neural network-based optical channel equalizers, we demonstrate that the performance of the biLSTM equalizer with approximated activation functions is close to that of the original model.

Cite

@article{arxiv.2305.09495,
  title  = {Hardware Realization of Nonlinear Activation Functions for NN-based Optical Equalizers},
  author = {Sasipim Srivallapanondh and Pedro J. Freire and Antonio Napoli and Sergei K. Turitsyn and Jaroslaw E. Prilepsky},
  journal= {arXiv preprint arXiv:2305.09495},
  year   = {2023}
}

Comments

2 pages, 1 figure, 1 table, Conference on Lasers & Electro-Optics 2023

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