@inproceedings{16b2373633884fe482615245521723b4,
title = "Deep learning with synthetic photonic lattices for equalization in optical transmission systems",
abstract = "In this work we propose a new physical realization of optical neural network (ONN) based on a recently appeared technological platform of synthetic photonic lattices (SPL), and demonstrate its capabilities for deep learning. The system operates with time series of optical pulses with ability to easily control their parameters and possesses the architecture that well suits the ONN paradigm. We have also shown that such an ONN can be potentially utilized for signal processing in optical communication lines for signal distortion compensation.",
keywords = "Deep learning, Optical Transmission Systems, Synthetic Photonic Lattices",
author = "Pankov, {Artem V.} and Sidelnikov, {Oleg S.} and Vatnik, {Ilya D.} and Sukhorukov, {Andrey A.} and Churkin, {Dmitriy V.}",
note = "Publisher Copyright: {\textcopyright} 2019 SPIE.; Real-Time Photonic Measurements, Data Management, and Processing IV 2019 ; Conference date: 22-10-2019 Through 23-10-2019",
year = "2019",
doi = "10.1117/12.2537462",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Ming Li and Bahram Jalali and Asghari, {Mohammad Hossein}",
booktitle = "Real-Time Photonic Measurements, Data Management, and Processing IV",
address = "United States",
}