Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

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

Not Accessible

Your library or personal account may give you access

Abstract

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.

© 2024 The Author(s)

PDF Article
More Like This
Spiking Neural Network Decision Feedback Equalization for IM/DD Systems

Alexander von Bank, Eike-Manuel Edelmann, and Laurent Schmalen
JW2E.3 Integrated Photonics Research, Silicon and Nanophotonics (IPR) 2023

Spiking Neural Network Equalization on Neuromorphic Hardware for IM/DD Optical Communication

Elias Arnold, Georg Böcherer, Eric Müller, Philipp Spilger, Johannes Schemmel, Stefano Calabrò, and Maxim Kuschnerov
Th1C.5 European Conference and Exhibition on Optical Communication (ECOC) 2022

Spiking Neural Network Linear Equalization: Experimental Demonstration of 2km 100Gb/s IM/DD PAM4 Optical Transmission

Georg Böcherer, Florian Strasser, Elias Arnold, Youxi Lin, Johannes Schemmel, Stefano Calabrò, and Maxim Kuschnerov
W4E.1 Optical Fiber Communication Conference (OFC) 2023

Poster Presentation

Media 1: PDF (168 KB)     
Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.