# Revisiting Multi-Step Nonlinearity Compensation with Machine Learning

arXiv: https://arxiv.org/abs/1904.09807 · HTML: https://mlsanity.com/paper/1904.09807/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Apr 2019.

## Built on by (most cited first, 1 of 1)

- [Computational Complexity Evaluation of Neural Network Applications in Signal Processing](https://mlsanity.com/paper/2206.12191/) (2022)

## Abstract (arXiv)

For the efficient compensation of fiber nonlinearity, one of the guiding principles appears to be: fewer steps are better and more efficient. We challenge this assumption and show that carefully designed multi-step approaches can lead to better performance-complexity trade-offs than their few-step counterparts.