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 …

We present the fundamentals of multiple-input, multiple-output (MIMO) signal processing for
mode-division multiplexing (MDM) in multimode fiber (MMF). As an introduction, we review …

The design of application-specific integrated circuits (ASIC) is at the core of modern ultra-
high-speed transponders employing advanced digital signal processing (DSP) algorithms …

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 …

A paradigm shift in optical communication networks is proposed, with the introduction of a
new ecosystem of devices and components with the capability of transforming current point …

A physics‐informed neural network (PINN) that combines deep learning with physics is
studied to solve the nonlinear Schrödinger equation for learning nonlinear dynamics in fiber …

Advances in High-Speed DACs, ADCs, and DSP for Optical Coherent Transceivers Page 1
JOURNAL OF LIGHTWAVE TECHNOLOGY, VOL. 32, NO. 4, FEBRUARY 15, 2014 629 …

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 …

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 …

Nonlinearity compensation is considered as a key enabler to increase channel transmission
rates in the installed optical communication systems. Recently, data-driven approaches …