Neuromorphic information processing using silicon photonics
| dc.contributor.author | Bienstman, Peter | |
| dc.contributor.author | Dambre, Joni | |
| dc.contributor.author | Katumba, Andrew | |
| dc.contributor.author | Freiberger, Matthias | |
| dc.contributor.author | Laporte, Floris | |
| dc.date.accessioned | 2022-11-30T20:33:15Z | |
| dc.date.available | 2022-11-30T20:33:15Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | We present our latest results on silicon photonics neuromorphic information processing based a.o. on techniques like reservoir computing. First, we dicuss how passive reservoir computing can be used to perform non-linear signal equalisation in telecom links. Then, we introduce a training method that can deal with limited weight resolution for a hardware implementation of a photonic readout. | en_US |
| dc.identifier.citation | Peter Bienstman, Joni Dambre, Andrew Katumba, Matthias Freiberger, Floris Laporte, Alessio Lugnan, Stijn Sackesyn, Chonghuai Ma, "Neuromorphic information processing using silicon photonics," Proc. SPIE 11081, Active Photonic Platforms XI, 110811I (5 September 2019); doi: | en_US |
| dc.identifier.other | 10.1117/12.2524707 | |
| dc.identifier.uri | https://nru.uncst.go.ug/handle/123456789/5585 | |
| dc.language.iso | en | en_US |
| dc.publisher | IEEE Journal of Selected Topics in Quantum Electronics | en_US |
| dc.subject | Photonic neuromorphic information processing | en_US |
| dc.subject | Reservoir computing | en_US |
| dc.subject | Silicon photonics | en_US |
| dc.title | Neuromorphic information processing using silicon photonics | en_US |
| dc.type | Article | en_US |
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