Artificial neural networks for photonic applications—from algorithms to implementation: tutorial

P Freire, E Manuylovich, JE Prilepsky… - Advances in Optics and …, 2023 - opg.optica.org
This tutorial–review on applications of artificial neural networks in photonics targets a broad
audience, ranging from optical research and engineering communities to computer science …

Machine learning for intelligent optical networks: A comprehensive survey

R Gu, Z Yang, Y Ji - Journal of Network and Computer Applications, 2020 - Elsevier
With the rapid development of Internet and communication systems, both in the aspect of
services and technologies, communication networks have been suffering increasing …

Flexible technologies to increase optical network capacity

A Lord, SJ Savory, M Tornatore… - Proceedings of the …, 2022 - ieeexplore.ieee.org
Increased global traffic puts tough requirements not just on fiber communications links but
on the entire network. This manifests itself in multiple ways, including how to optimize …

Fiber-longitudinal anomaly position identification over multi-span transmission link out of receiver-end signals

T Tanimura, S Yoshida, K Tajima, S Oda… - Journal of Lightwave …, 2020 - opg.optica.org
We have developed a fiber-longitudinal monitor that visualizes distance-wise optical power
throughout the entire multi-span link by using the signal waveform obtained by a coherent …

Machine learning applications for short reach optical communication

Y Xie, Y Wang, S Kandeepan, K Wang - Photonics, 2022 - mdpi.com
With the rapid development of optical communication systems, more advanced techniques
conventionally used in long-haul transmissions have gradually entered systems covering …

Machine learning techniques in optical networks: a systematic mapping study

G Villa, C Tipantuña, DS Guamán, GV Arévalo… - IEEE …, 2023 - ieeexplore.ieee.org
During the last decade, optical networks have become “smart networks”. Software-defined
networks, software-defined optical networks, and elastic optical networks are some …

Non-technological barriers: the last frontier towards AI-powered intelligent optical networks

FN Khan - Nature Communications, 2024 - nature.com
Abstract Machine learning (ML) has been remarkably successful in transforming numerous
scientific and technological fields in recent years including computer vision, natural …

AI-based modeling and monitoring techniques for future intelligent elastic optical networks

X Liu, H Lun, M Fu, Y Fan, L Yi, W Hu, Q Zhuge - Applied Sciences, 2020 - mdpi.com
With the development of 5G technology, high definition video and internet of things, the
capacity demand for optical networks has been increasing dramatically. To fulfill the capacity …

Cost-effective and data size–adaptive OPM at intermediated node using convolutional neural network-based image processor

D Wang, M Wang, M Zhang, Z Zhang, H Yang, J Li… - Optics express, 2019 - opg.optica.org
A cost-effective and data size-adaptive optical performance monitoring (OPM) scheme is
proposed, which is based on asynchronous delay-tap plot (ADTP) using convolutional …

Soft failure identification for long-haul optical communication systems based on one-dimensional convolutional neural network

H Lun, M Fu, X Liu, Y Wu, L Yi, W Hu… - Journal of Lightwave …, 2020 - opg.optica.org
With the advance of elastic optical networks, optical communication systems are becoming
more flexible and dynamic. In this scenario, soft failures are more likely to occur due to …