Please use this identifier to cite or link to this item:
http://cris.utm.md/handle/5014/558
Title: | Optical reservoir computing: prospects of using sub-10 picosecond lasers | Authors: | BURLACU, Alexandru | Keywords: | reservoir computing;machine learning;optical computing;InGaN lasers | Issue Date: | 2020 | Source: | BURLACU, Alexandru. Optical reservoir computing: prospects of using sub-10 picosecond lasers. In: Conferinţa tehnico-ştiinţifică a studenţilor, masteranzilor şi doctoranzilor. Volumul I, 1-3 aprilie 2020, Chișinău. Chișinău, Republica Moldova: 2020, pp. 262-264. ISBN 978-9975-45-632-6. | Project: | 20.80009.5007.08. Studiul structurilor optoelectronice şi a dispozitivelor termoelectrice cu eficienţă înaltă | Conference: | Conferinţa tehnico-ştiinţifică a studenţilor, masteranzilor şi doctoranzilor 2020 | 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. |
URI: | https://ibn.idsi.md/ro/vizualizare_articol/106402 http://cris.utm.md/handle/5014/558 |
ISBN: | 978-9975-45-632-6 |
Appears in Collections: | Conference Abstracts |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
262-264_4.pdf | 217.5 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.