Machine learning techniques for optical communication system optimization

Darko Zibar; Jesper Wass; Jakob Thrane; Molly Piels

doi:10.1109/ICTON.2017.8025039

Machine learning techniques for optical communication system optimization

Darko Zibar, Jesper Wass, Jakob Thrane, Molly Piels

Centre of Excellence for Silicon Photonics for Optical Communications

Technical University of Denmark

Research output: Contribution to conference › Conference abstract for conference › Research › peer-review

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Abstract

In this paper, machine learning techniques relevant to optical communication are presented and discussed. The focus is on applying machine learning tools to optical performance monitoring and performance prediction.

Original language	English
Publication date	2017
Number of pages	1
DOIs	https://doi.org/10.1109/ICTON.2017.8025039
Publication status	Published - 2017
Event	19th International Conference on Transparent Optical Networks - Girona, Spain Duration: 2 Jul 2017 → 6 Jul 2017

Conference

Conference	19th International Conference on Transparent Optical Networks
Country/Territory	Spain
City	Girona
Period	02/07/2017 → 06/07/2017

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title = "Machine learning techniques for optical communication system optimization",

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year = "2017",

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AU - Zibar, Darko

AU - Wass, Jesper

AU - Thrane, Jakob

AU - Piels, Molly

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N2 - In this paper, machine learning techniques relevant to optical communication are presented and discussed. The focus is on applying machine learning tools to optical performance monitoring and performance prediction.

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M3 - Conference abstract for conference

T2 - 19th International Conference on Transparent Optical Networks

Y2 - 2 July 2017 through 6 July 2017

ER -

Machine learning techniques for optical communication system optimization

Abstract

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