Author:
Sedov E.V.,Chekhovskoy I.S.,Prilepsky J.E.
Abstract
Abstract
A neural network architecture is proposed that allows a continuous nonlinear spectrum of optical signals to be predicted and an inverse nonlinear Fourier transform (NFT) to be performed for signal modulation. The average value of the relative error in predicting the continuous spectrum by the neural network when calculating the direct NFT is found to be 2.68 × 10−3, and the average value of the relative error in predicting the signal for the inverse NFT is 1.62 × 10−4.
Subject
Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics,Statistical and Nonlinear Physics,Electronic, Optical and Magnetic Materials
Cited by
5 articles.
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