Artificial neural networks for photonic applications—from algorithms to implementation: tutorial
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 …
audience, ranging from optical research and engineering communities to computer science …
Neural networks-based equalizers for coherent optical transmission: Caveats and pitfalls
This paper performs a detailed, multi-faceted analysis of key challenges and common
design caveats related to the development of efficient neural networks (NN) based nonlinear …
design caveats related to the development of efficient neural networks (NN) based nonlinear …
Recurrent Neural Networks and Recurrent Optical Spectrum Slicers as Equalizers in High Symbol Rate Optical Transmission Systems
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 …
covering the immense and increasing traffic demands created. This ecosystem also seeks …
Neural network-aided receivers for soliton communication impaired by solitonic interaction
Y Chen, M Baniasadi, M Safari - Optics Express, 2023 - opg.optica.org
In this paper, different neural network-based methods are proposed to improve the
achievable information rate in amplitude-modulated soliton communication systems. The …
achievable information rate in amplitude-modulated soliton communication systems. The …
Experimental implementation of a neural network optical channel equalizer in restricted hardware using pruning and quantization
The deployment of artificial neural networks-based optical channel equalizers on edge-
computing devices is critically important for the next generation of optical communication …
computing devices is critically important for the next generation of optical communication …
Attention-aided partial bidirectional RNN-based nonlinear equalizer in coherent optical systems
We leverage the attention mechanism to investigate and comprehend the contribution of
each input symbol of the input sequence and their hidden representations for predicting the …
each input symbol of the input sequence and their hidden representations for predicting the …
Blind channel equalization using vector-quantized variational autoencoders
State-of-the-art high-spectral-efficiency communication systems employ high-order
modulation formats coupled with high symbol rates to accommodate the ever-growing …
modulation formats coupled with high symbol rates to accommodate the ever-growing …
Gesture Classification in Electromyography Signals for Real-Time Prosthetic Hand Control Using a Convolutional Neural Network-Enhanced Channel Attention Model
G Yu, Z Deng, Z Bao, Y Zhang, B He - Bioengineering, 2023 - mdpi.com
Accurate and real-time gesture recognition is required for the autonomous operation of
prosthetic hand devices. This study employs a convolutional neural network-enhanced …
prosthetic hand devices. This study employs a convolutional neural network-enhanced …
A Data-Driven Digital Demodulator Based on Deep Learning for Radio Over Fiber Transmission System
A data-driven digital demodulator based on a Fourier layer Transformer network (FTnet) for
radio over fiber (RoF) transmission system with quadrature amplitude modulation (QAM) is …
radio over fiber (RoF) transmission system with quadrature amplitude modulation (QAM) is …
Finite-Genus Solutions-based Optical Communication with the Riemann-Hilbert Problem Transmitter and a Convolutional Neural Network Receiver
S Bogdanov, D Shepelsky… - Journal of Lightwave …, 2024 - ieeexplore.ieee.org
In the study, we develop a new optical communication system based on the nonlinear
Fourier transform for generic (quasiperiodic) finite-genus solutions to the nonlinear …
Fourier transform for generic (quasiperiodic) finite-genus solutions to the nonlinear …