In the era of the Internet of Things (IoT), an enormous amount of sensing devices collect
and/or generate various sensory data over time for a wide range of fields and applications …

Hot tearing is one of the most severe and irreversible casting defects for many metallic
materials. In 2004, Eskin et al. published a review paper in which the development of hot …

We present the results of the comparative performance-versus-complexity analysis for the
several types of artificial neural networks (NNs) used for nonlinear channel equalization in …

In this paper, we implement an optical fiber communication system as an end-to-end deep
neural network, including the complete chain of transmitter, channel model, and receiver …

Artificial Neural Networks is a calculation method that builds several processing units based
on interconnected connections. The network consists of an arbitrary number of cells or …

We extend the idea of end-to-end learning of communications systems through deep neural
network (NN)-based autoencoders to orthogonal frequency division multiplexing (OFDM) …

We propose a new machine-learning approach for fiber-optic communication systems
whose signal propagation is governed by the nonlinear Schrödinger equation (NLSE). Our …

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 …

Abstract Machine learning techniques have proven very efficient in assorted classification
tasks. Nevertheless, processing time-dependent high-speed signals can turn into an …

We introduce for the first time the utilization of Long short-term memory (LSTM) neural
network architectures for the compensation of fiber nonlinearities in digital coherent systems …