Journal
OPTICS EXPRESS
Volume 26, Issue 25, Pages 32765-32776Publisher
OPTICAL SOC AMER
DOI: 10.1364/OE.26.032765
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Funding
- Russian Science Foundation [17-72-30006]
- EPSRC project TRANSNET [EP/R035342/1]
- EPSRC [EP/R035342/1] Funding Source: UKRI
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We investigate the application of dynamic deep neural networks for nonlinear equalization in long haul transmission systems. Through extensive numerical analysis we identify their optimum dimensions and calculate their computational complexity as a function of system length. Performing comparison with traditional back-propagation based nonlinear compensation of 2 steps-per-span and 2 samples-per-symbol, we demonstrate equivalent mitigation performance at significantly lower computational cost. (C) 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
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