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 …

The transition to the edge-cloud era makes ultra-high data rate signals indispensable for
covering the immense and increasing traffic demands created. This ecosystem also seeks …

Knowledge Distillation Applied to Optical Channel Equalization: Solving the Parallelization
Problem of Recurrent Connection Page 1 Knowledge Distillation Applied to Optical Channel …

We develop a method for retrieving a set of parameters of a quasi-periodic finite-genus
(finite-gap) solution to the focusing nonlinear Schrödinger (NLS) equation, given the solution …

The recurrent neural network (RNN)-based equalizers, especially the bidirectional long-
short-term memory (biLSTM) structure, have already been proven to outperform the feed …

In this work, we demonstrate the offline FPGA realization of both recurrent and feedforward
neural network (NN)-based equalizers for nonlinearity compensation in coherent optical …

In this paper, we introduce a new nonlinear channel equalization method for the coherent
long-haul transmission based on Transformers. We show that due to their capability to …

Vehicle-to-everything (V2X) networks will constitute a prominent application in future
generations of cellular networks, definitely transforming our conception of transportation …

Kerr nonlinearity in the form of self-and cross-phase modulation imposes a fundamental
limitation to the capacity of wavelength division multiplexed (WDM) optical communication …