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 …

Experimental results based on offline processing reported at optical conferences
increasingly rely on neural network-based equalizers for accurate data recovery. However …

In this paper, we provide a systematic approach for assessing and comparing the
computational complexity of neural network layers in digital signal processing. We provide …

Fiber Kerr nonlinearity is a fundamental limitation to the achievable capacity of long-distance
optical fiber communication. Digital back-propagation (DBP) is a primary methodology to …

In this work, we address the question of the adaptability of artificial neural networks (NNs)
used for impairments mitigation in optical transmission systems. We demonstrate that by …

This paper introduces a novel methodology for developing low-complexity neural network
(NN) based equalizers to address impairments in high-speed coherent optical transmission …

With the emergence of new services, the complex optical network environment makes it
more difficult to predict network anomalies. This paper proposes a multi-index anomaly …

Over the last decades, the aspect-based sentiment analysis (ABSA) task has been given
great attention and has been deeply studied by the scientific community. It was first …

To meet the demand of emerging applications, such as fixed-mobile convergence for the fifth
generation of mobile networks and beyond, a 100-Gbit/s/λ access network becomes the next …

In this work, a perturbation-based neural network (P-NN) scheme with an embedded
bidirectional long short-term memory (biLSTM) layer is investigated to compensate for the …