Predicting optical power excursions in erbium doped fiber amplifiers using neural networks

Abstract : We report on a Machine Learning approach based on artificial Neural Networks to predict optical power excursion in Erbium Doped Fiber Amplifiers. Its flexibility and adaptability could be valuable for future optical networks dealing with the negative impact of this aforementioned physical layer impairment
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01980287
Contributor : Médiathèque Télécom Sudparis & Institut Mines-Télécom Business School <>
Submitted on : Monday, January 14, 2019 - 12:17:33 PM
Last modification on : Tuesday, February 26, 2019 - 11:36:17 AM

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Maria José Freire Hermelo, Sébastien Mansfeld, Djamel Amar, Franck Gillet, Antoine Lavignotte, et al.. Predicting optical power excursions in erbium doped fiber amplifiers using neural networks. ACP 2018 : Asia Communication and Photonics Conference, Oct 2018, Hangzhou, China. IEEE Computer Society, Proceedings ACP 2018 : Asia Communication and Photonics Conference, pp.1 - 3, 2018, 〈10.1109/ACP.2018.8596233〉. 〈hal-01980287〉

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