| Authors: | P. Bienstman, J. Dambre, A. Katumba, M. Freiberger, F. Laporte, A. Lugnan | | Title: | Photonic reservoir computing: a brain-inspired approach for information processing | | Format: | International Conference Proceedings | | Publication date: | 3/2018 | | Journal/Conference/Book: | The Optical Fiber Communication Conference (OFC)
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| | Editor/Publisher: | Optical Society of America, | | Volume(Issue): | p.paper M4F.4 (3 pages) | | Location: | San Diego, United States | | DOI: | 10.1364/OFC.2018.M4F.4 | | Citations: | 3 (Dimensions.ai - last update: 17/11/2024)
1 (OpenCitations - last update: 27/6/2024)
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Abstract
We present our latest results on silicon photonics neuromorphic information processing
based on techniques like reservoir computing. We will discuss aspects like scalability,
novel architectures for enhanced power efficiency, as well as all-optical readout. Additionally,
we will touch upon new machine learning techniques to operate these integrated readouts. Related Research Topics
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