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 …

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 …

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 …

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 …

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 paper, we introduce a new nonlinear optical channel equalizer based on
Transformers. By leveraging parallel computation and attending directly to the memory …

An artificial neural network is very important to the design and analysis of any complex
algorithm and process. In this paper, a photonic artificial neuron is designed using Arduino …

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