O. Kotlyar, Morteza Kamalian Kopae, J. Prilepsky, M. Pankratova, S. Turitsyn
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Machine learning for performance improvement of periodic NFT-based communication system
We compare performance of several machine learning methods, including support vector machine, k-nearest neighbours, k-means clustering, and Gaussian mixture model, used for increasing transmission reach in the optical communication system based on the periodic nonlinear Fourier transform signal processing
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