Abstract

We propose a digital incoherent optical neural network architecture using the passive data routing and copying capabilities of optics for artificial neural network acceleration. We demonstrate a proof-of-concept experiment and analyze optimal use cases.

© 2020 The Author(s)

PDF Article  |   Presentation Video
More Like This
Large-scale optical neural network with high-speed learning

Yutaka Yagai, Toyohiko Yatagai, Masahiko Mori, and Masanobu Watanabe
OThD4 Optics in Computing (OC) 1999

Large-Scale Optical Neural-Network Accelerators based on Coherent Detection

Ryan Hamerly, Alex Sludds, Liane Bernstein, Marin Soljačić, and Dirk Englund
JF2F.5 CLEO: Applications and Technology (CLEO_AT) 2019

Machine Learning for Cognitive Optical Network Security Management

Marija Furdek and Carlos Natalino
NeW1B.3 Photonic Networks and Devices (Networks) 2020

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Presentation Video

Conference videos freely accessible until 30 June 2021 and available to subscribers only thereafter.

More Like This
Large-scale optical neural network with high-speed learning

Yutaka Yagai, Toyohiko Yatagai, Masahiko Mori, and Masanobu Watanabe
OThD4 Optics in Computing (OC) 1999

Large-Scale Optical Neural-Network Accelerators based on Coherent Detection

Ryan Hamerly, Alex Sludds, Liane Bernstein, Marin Soljačić, and Dirk Englund
JF2F.5 CLEO: Applications and Technology (CLEO_AT) 2019

Machine Learning for Cognitive Optical Network Security Management

Marija Furdek and Carlos Natalino
NeW1B.3 Photonic Networks and Devices (Networks) 2020