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

arXiv 2305.09495 ↗First posted 16 May 2023cs.LG physics.opticscited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 2 of its 7 references that are in the map. First posted on arXiv 16 May 2023.

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References · 2

  1. 2021Performance versus Complexity Study of Neural Network Equalizers in Coherent Optical Systemscited by 17
  2. 2022Towards FPGA Implementation of Neural Network-Based Nonlinearity Mitigation Equalizers in Coherent Optical Transmission Systemscited by 4

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