# Stochastic resonance neurons in artificial neural networks

arXiv: https://arxiv.org/abs/2205.10122 · HTML: https://mlsanity.com/paper/2205.10122/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 18 references that are in the map.
- First posted on arXiv 6 May 2022.

## Builds on (most cited first, 1 of 1)

- [Analyzing noise in autoencoders and deep networks](https://mlsanity.com/paper/1406.1831/) (2014)

## Abstract (arXiv)

Many modern applications of the artificial neural networks ensue large number of layers making traditional digital implementations increasingly complex. Optical neural networks offer parallel processing at high bandwidth, but have the challenge of noise accumulation. We propose here a new type of neural networks using stochastic resonances as an inherent part of the architecture and demonstrate a possibility of significant reduction of the required number of neurons for a given performance accuracy. We also show that such a neural network is more robust against the impact of noise.