Energy-efficient Spiking Neural Network Equalization for IM/DD Systems with Optimized Neural Encoding

Autor:	von Bank, Alexander, Edelmann, Eike-Manuel, Schmalen, Laurent
Rok vydání:	2023
Předmět:	Electrical Engineering and Systems Science - Signal Processing Computer Science - Machine Learning Computer Science - Neural and Evolutionary Computing
Druh dokumentu:	Working Paper
Popis:	We propose an energy-efficient equalizer for IM/DD systems based on spiking neural networks. We optimize a neural spike encoding that boosts the equalizer's performance while decreasing energy consumption. Comment: Accepted for publication at OFC 2024
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2312.12909 Zobrazit plný text záznamu View this record from Arxiv