Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • 2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference
  • OSA Technical Digest (Optica Publishing Group, 2019),
  • paper jsi_2_4

Reinforcement Learning in a Large Scale Photonic Network

Not Accessible

Your library or personal account may give you access

Abstract

In recent years Neural Networks or Neuromorphic Computing has significantly shifted the limits of what is computationally possible [1]. Recurrent Neural Networks are nonlinear dynamical systems, and as such they are inherently capable to process temporal information or signals. They show excellent performance in the prediction of chaotic trajectories or in the equalization of nonlinearly corrupted communication channels [2].

© 2019 IEEE

PDF Article
More Like This
Reinforcement Learning in a Large Scale Photonic Network

Louis Andreoli, Sheler Maktoobi, Laurent Larger, Maxime Jacquot, Xavier Porte, and Daniel Brunner
NTh1A.2 Nonlinear Optics (NLO) 2019

Reinforcement Learning in a Large Scale Photonic Network

Daniel Brunner, Maxime Jacquot, Ingo Fischer, and Laurent Larger
W2A.2 Latin America Optics and Photonics Conference (LAOP) 2018

Reinforcement Learning in a Large Scale Photonic Network

Sheler Maktoobi, Louis Andreoli, Laurent Larger, Maxime Jacquot, and Daniel Brunner
W1D.4 Conference on Lasers and Electro-Optics/Pacific Rim (CLEO/PR) 2018

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved