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This article is cited in 9 scientific papers (total in 9 papers)
Fibreoptic communication lines
Use of complex fully connected neural networks to compensate for nonlinear effects in fibre-optic communication lines
S. A. Bogdanov, O. S. Sidelnikov Novosibirsk State University
Abstract:
A scheme is proposed for processing optical signals in a receiver of a communication system, based on complex fully connected neural networks. The influence of the main characteristics of the neural network on the efficiency of nonlinear distortion compensation is studied. A significant advantage of the proposed scheme over real-valued neural networks is demonstrated.
Keywords:
optical fibre, nonlinear effects, fully connected neural networks, mathematical modelling.
Received: 28.12.2020 Revised: 27.02.2021
Citation:
S. A. Bogdanov, O. S. Sidelnikov, “Use of complex fully connected neural networks to compensate for nonlinear effects in fibre-optic communication lines”, Kvantovaya Elektronika, 51:5 (2021), 459–462 [Quantum Electron., 51:5 (2021), 459–462]
Linking options:
https://www.mathnet.ru/eng/qe17436 https://www.mathnet.ru/eng/qe/v51/i5/p459
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Abstract page: | 122 | Full-text PDF : | 50 | References: | 22 | First page: | 11 |
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