Silicon photonics for neuromorphic information processing

Simple item page
dc.contributor.authorBienstman, Peter
dc.contributor.authorDambre, Joni
dc.contributor.authorKatumba, Andrew
dc.contributor.authorFreiberger, Matthias
dc.contributor.authorLaporte, Floris
dc.contributor.authorLugnan, Alessio
dc.date.accessioned2022-12-01T18:38:13Z
dc.date.available2022-12-01T18:38:13Z
dc.date.issued2018
dc.description.abstractWe present our latest results on silicon photonics neuromorphic information processing based a.o. on techniques like reservoir computing. We will discuss aspects like scalability, novel architectures for enhanced power e ciency, as well as all-optical readout. Additionally, we will touch upon new machine learning techniques to operate these integrated readouts. Finally, we will show how these systems can be used for high-speed low-power information processing for applications like recognition of biological cells.en_US
dc.identifier.citationPeter Bienstman, Joni Dambre, Andrew Katumba, Matthias Freiberger, Floris Laporte, Alessio Lugnan, "Silicon photonics for neuromorphic information processing," Proc. SPIE 10551, Optical Data Science: Trends Shaping the Future of Photonics, 105510K (14 February 2018); doi: 10.1117/12.2284391en_US
dc.identifier.other10.1117/12.2284391
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/5632
dc.language.isoenen_US
dc.publisherSPIEen_US
dc.subjectPhotonic neuromorphic information processingen_US
dc.subjectReservoir computingen_US
dc.titleSilicon photonics for neuromorphic information processingen_US
dc.typeOtheren_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Silicon photonics for neuromorphic.pdf
Size:
420.17 KB
Format:
Adobe Portable Document Format
Description:
Conference Paper
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Engineering and Technology