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arxiv: 2109.08711 · v1 · pith:6A3GVKJH · submitted 2021-09-17 · eess.SP · cs.LG

Experimental Evaluation of Computational Complexity for Different Neural Network Equalizers in Optical Communications

Pedro J. Freire , Yevhenii Osadchuk , Antonio Napoli , Bernhard Spinnler , Wolfgang Schairer , Nelson Costa , Jaroslaw E. Prilepsky , Sergei K. Turitsyn This is my paper

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classification eess.SP cs.LG
keywords neuralcomplexityequalizersnetworkopticaladdressinganalysisarchitectures
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Addressing the neural network-based optical channel equalizers, we quantify the trade-off between their performance and complexity by carrying out the comparative analysis of several neural network architectures, presenting the results for TWC and SSMF set-ups.

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