Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Deep Neural Networks with Time-Domain Synthetic Photonic Lattices. / Pankov, Artem V.; Sidelnikov, Oleg S.; Vatnik, Ilya D. et al.
2021 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. (2021 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2021).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
}
TY - GEN
T1 - Deep Neural Networks with Time-Domain Synthetic Photonic Lattices
AU - Pankov, Artem V.
AU - Sidelnikov, Oleg S.
AU - Vatnik, Ilya D.
AU - Churkin, Dmitry V.
AU - Sukhorukov, Andrey A.
N1 - Funding Information: This work is supported by Ministry of Education and Science of the Russian Federation (FSUS-2020-0034) and the Australian Research Council (DP190100277). Publisher Copyright: © 2021 IEEE.
PY - 2021/6
Y1 - 2021/6
N2 - Optical neural networks (ONN) attracts a lot of attention based on their potential to offer orders-of-magnitude faster performance and lower energy consumption compared to purely electronic systems. There are strong advances in processing of spatially- and frequency-encoded optical data [1]. However the ONN development for coherent manipulation of optical pulse trains remains an open challenge, which could lead to advances in communications and real-time data analysis.
AB - Optical neural networks (ONN) attracts a lot of attention based on their potential to offer orders-of-magnitude faster performance and lower energy consumption compared to purely electronic systems. There are strong advances in processing of spatially- and frequency-encoded optical data [1]. However the ONN development for coherent manipulation of optical pulse trains remains an open challenge, which could lead to advances in communications and real-time data analysis.
UR - http://www.scopus.com/inward/record.url?scp=85117588665&partnerID=8YFLogxK
U2 - 10.1109/CLEO/Europe-EQEC52157.2021.9542271
DO - 10.1109/CLEO/Europe-EQEC52157.2021.9542271
M3 - Conference contribution
AN - SCOPUS:85117588665
T3 - 2021 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2021
BT - 2021 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2021
Y2 - 21 June 2021 through 25 June 2021
ER -
ID: 34538125