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
Type de document :
Communication dans un congrès
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〉
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https://hal.archives-ouvertes.fr/hal-01980287
Contributeur : Médiathèque Télécom Sudparis & Institut Mines-Télécom Business School <>
Soumis le : lundi 14 janvier 2019 - 12:17:33
Dernière modification le : mardi 22 janvier 2019 - 14:32:09

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Citation

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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