| Authors: | P. Bienstman, J. Dambre, A. Katumba, M. Freiberger, F. Laporte, A. Lugnan | | Title: | Silicon photonics for neuromorphic information processing | | Format: | International Conference Proceedings | | Publication date: | 1/2018 | | Journal/Conference/Book: | SPIE Photonics West
(invited)
| | Editor/Publisher: | SPIE, | | Volume(Issue): | DL 10551 p.paper 10551-19 (7 pages) | | Location: | San Francisco, United States | | DOI: | 10.1117/12.2284391 | | Citations: | Look up on Google Scholar
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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 efficiency, 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 telecommunications and recognition of biological cells. Related Research Topics
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