High speed time series prediction with a photonic spiking neural network built with a single VCSEL

D. Owen-Newns, L. Jaurigue, J. Robertson, A. Adair, J. Jaurigue, K. Lüdge, A. Hurtado

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

We report a high speed Neuromorphic Photonic Spiking Neural Network (p-SNN) built with a Vertical Cavity Surface Emitting Laser (VCSEL). Memory is induced in the p-SNN by introducing two separate past points in the time series allowing accurate predictions over a range of future horizons.
Original languageEnglish
Title of host publication2024 IEEE Photonics Conference (IPC)
PublisherIEEE
Pages1-2
Number of pages2
ISBN (Electronic)979-8-3503-6195-7
ISBN (Print)979-8-3503-6196-4
DOIs
Publication statusPublished - 20 Dec 2024
EventIEEE Photonics Conference 2024 - Rome, Italy
Duration: 10 Nov 202414 Nov 2024
https://ieee-ipc.org/

Publication series

Name2024 IEEE Photonics Conference (IPC)
PublisherIEEE
ISSN (Print)2374-0140
ISSN (Electronic)2575-274X

Conference

ConferenceIEEE Photonics Conference 2024
Abbreviated titleIPC
Country/TerritoryItaly
CityRome
Period10/11/2414/11/24
Internet address

Funding

The authors acknowledge support by the UKRI Turing AI Acceleration Fellowships Programme (EP/V025198/1), and by the EU Pathfinder Open project ‘SpikePro’. The authors acknowledge support from the Fraunhofer Centre for Applied Photonics, FCAP.

Keywords

  • VCSELs
  • Neuromorphic Photonics
  • Spiking Neural Networks
  • Semiconductor Lasers

Cite this