A Multiple-Input Strategy to Efficient Integrated Photonic Reservoir Computing

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dc.contributor.authorKatumba, Andrew
dc.contributor.authorFreiberger, Matthias
dc.contributor.authorBienstman, Peter
dc.contributor.authorDambre, Joni
dc.date.accessioned2022-11-27T16:49:26Z
dc.date.available2022-11-27T16:49:26Z
dc.date.issued2017
dc.description.abstractPhotonic 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.en_US
dc.identifier.citationKatumba, A., Freiberger, M., Bienstman, P., & Dambre, J. (2017). A multiple-input strategy to efficient integrated photonic reservoir computing. Cognitive Computation, 9(3), 307-314.en_US
dc.identifier.urihttps://link.springer.com/article/10.1007/s12559-017-9465-5
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/5482
dc.language.isoenen_US
dc.publisherCognitive Computation,en_US
dc.subjectReservoir Computingen_US
dc.subjectIntegrated Pho- tonicsen_US
dc.subjectPhotonic Reservoir Computingen_US
dc.subjectReservoir Architecturesen_US
dc.titleA Multiple-Input Strategy to Efficient Integrated Photonic Reservoir Computingen_US
dc.typeArticleen_US
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