# Neural Network Decoders for Permutation Codes Correcting Different Errors

arXiv: https://arxiv.org/abs/2206.03315 · HTML: https://mlsanity.com/paper/2206.03315/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 11 of its 40 references that are in the map.
- First posted on arXiv 7 Jun 2022.

## Builds on (most cited first, 11 of 11)

- [Deep Learning Methods for Improved Decoding of Linear Codes](https://mlsanity.com/paper/1706.07043/) (2017)
- [Learning to Decode Linear Codes Using Deep Learning](https://mlsanity.com/paper/1607.04793/) (2016)
- [Deep Learning for Decoding of Linear Codes - A Syndrome-Based Approach](https://mlsanity.com/paper/1802.04741/) (2018)
- [Neural Offset Min-Sum Decoding](https://mlsanity.com/paper/1701.05931/) (2017)
- [Pruning Neural Belief Propagation Decoders](https://mlsanity.com/paper/2001.07464/) (2020)
- [Learned Belief-Propagation Decoding with Simple Scaling and SNR Adaptation](https://mlsanity.com/paper/1901.08621/) (2019)
- [Deep Learning Based Sphere Decoding](https://mlsanity.com/paper/1807.03162/) (2018)
- [Active Deep Decoding of Linear Codes](https://mlsanity.com/paper/1906.02778/) (2019)
- [Performance Evaluation of Channel Decoding With Deep Neural Networks](https://mlsanity.com/paper/1711.00727/) (2017)
- [What Can Machine Learning Teach Us about Communications?](https://mlsanity.com/paper/1901.07592/) (2019)
- [Neural network approaches to point lattice decoding](https://mlsanity.com/paper/2012.07032/) (2020)

## Abstract (arXiv)

Permutation codes were extensively studied in order to correct different types of errors for the applications on power line communication and rank modulation for flash memory. In this paper, we introduce the neural network decoders for permutation codes to correct these errors with one-shot decoding, which treat the decoding as n classification tasks for non-binary symbols for a code of length n. These are actually the first general decoders introduced to deal with any error type for these two applications. The performance of the decoders is evaluated by simulations with different error models.