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

arXiv: https://arxiv.org/abs/2305.09495 · HTML: https://mlsanity.com/paper/2305.09495/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 7 references that are in the map.
- First posted on arXiv 16 May 2023.

## Builds on (most cited first, 2 of 2)

- [Performance versus Complexity Study of Neural Network Equalizers in Coherent Optical Systems](https://mlsanity.com/paper/2103.08212/) (2021)
- [Towards FPGA Implementation of Neural Network-Based Nonlinearity Mitigation Equalizers in Coherent Optical Transmission Systems](https://mlsanity.com/paper/2206.12180/) (2022)

## 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.