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Optical reservoir computing: prospects of using SUB-10 picosecond lasers

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dc.contributor.author ALEXANDRU, Burlacu
dc.date.accessioned 2020-06-03T10:19:12Z
dc.date.available 2020-06-03T10:19:12Z
dc.date.issued 2020
dc.identifier.citation ALEXANDRU, Burlacu. Optical reservoir computing: prospects of using SUB-10 picosecond lasers. In: Conferinţa tehnico-ştiinţifică a studenţilor, masteranzilor şi doctoranzilor = The Technical Scientific Conference of Undergraduate, Master and PhD Students, Universitatea Tehnică a Moldovei, 1-3 Aprilie, 2020. Chișinău, 2020, vol. 1, pp. 262-264. ISBN 978-9975-45-632-6. en_US
dc.identifier.isbn 978-9975-45-632-6
dc.identifier.uri http://repository.utm.md/handle/5014/8643
dc.description.abstract Training neural networks is hard. The industry is approaching the limits of siliconbased computing, both in terms of transistor size and chip dimensions. There are already examples of technologies that allow computations without using silicon. A paradigm for machine learning that could have enough representational power also exists. It is Reservoir Computing, which is also quite amenable for adaptation on non-silicon-based computing devices. In this work, I propose a specific type of laser-based reservoir computing scheme that builds on, and should improve, the existing solutions. en_US
dc.language.iso en en_US
dc.publisher Tehnica UTM en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject reservoir computing en_US
dc.subject machine learning en_US
dc.subject optical computing en_US
dc.subject picosecond lasers en_US
dc.subject lasers en_US
dc.title Optical reservoir computing: prospects of using SUB-10 picosecond lasers en_US
dc.type Article en_US


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