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eess.SP2024

Digital Twin of Industrial Networked Control System based on Value of Information

Van-Phuc Bui, Daniel Abode, Pedro M. de Sant Ana +3

The paper examines a scenario wherein sensors are deployed within an Industrial Networked Control System, aiming to construct a digital twin (DT) model for a remotely operated Auto…

eess.SP2022

Power Control for 6G Industrial Wireless Subnetworks: A Graph Neural Network Approach

Daniel Abode, Ramoni Adeogun, Gilberto Berardinelli

6th Generation (6G) industrial wireless subnetworks are expected to replace wired connectivity for control operation in robots and production modules. Interference management techn…

eess.SP2022

Domain Adaptation: the Key Enabler of Neural Network Equalizers in Coherent Optical Systems

Pedro J. Freire, Bernhard Spinnler, Daniel Abode +7

We introduce the domain adaptation and randomization approach for calibrating neural network-based equalizers for real transmissions, using synthetic data. The approach renders up…

eess.SP2021

Power and Modulation Format Transfer Learning for Neural Network Equalizers in Coherent Optical Transmission Systems

Pedro J. Freire, Daniel Abode, Jaroslaw E. Prilepsky +1

Transfer learning is proposed to adapt an NN-based nonlinear equalizer across different launch powers and modulation formats using a 450km TWC-fiber transmission. The result shows…

eess.SP2021

Transfer Learning for Neural Networks-based Equalizers in Coherent Optical Systems

Pedro J. Freire, Daniel Abode, Jaroslaw E. Prilepsky +4

In this work, we address the question of the adaptability of artificial neural networks (NNs) used for impairments mitigation in optical transmission systems. We demonstrate that b…