Silicon photonics for neuromorphic information processing
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Date
2018
Journal Title
Journal ISSN
Volume Title
Publisher
SPIE
Abstract
We 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.
Description
Keywords
Photonic neuromorphic information processing, Reservoir computing
Citation
Peter 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: 10.1117/12.2284391