A Multiple-Input Strategy to Efficient Integrated Photonic Reservoir Computing
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Date
2017
Authors
Katumba, Andrew
Freiberger, Matthias
Bienstman, Peter
Dambre, Joni
Journal Title
Journal ISSN
Volume Title
Publisher
Cognitive Computation,
Abstract
Photonic reservoir computing has evolved into a viable
contender for the next generation of analog computing
platforms as industry looks beyond standard transistor-based computing architectures. Integrated photonics reservoir computing, particularly on the Silicon-on-Insulator
platform, presents a CMOS-compatible, wide-bandwidth,
parallel platform for implementation of optical reservoirs. A number of demonstrations of the applicability
of this platform for processing optical telecommunications signals have been made in the recent past. In this
work, we take it a stage further by performing an architectural search for designs that yield the best performance while maintaining power efficiency.
Description
Keywords
Reservoir Computing, Integrated Pho- tonics, Photonic Reservoir Computing, Reservoir Architectures
Citation
Katumba, A., Freiberger, M., Bienstman, P., & Dambre, J. (2017). A multiple-input strategy to efficient integrated photonic reservoir computing. Cognitive Computation, 9(3), 307-314.