output
19992023
most citedReducing Computational Complexity of Neural Networks in Optical Channel Equalization: From Concepts to Implementation

58 citations

5 papers

eess.SP2023★ 1 cited

Multi-Task Learning to Enhance Generalizability of Neural Network Equalizers in Coherent Optical Systems

Sasipim Srivallapanondh, Pedro J. Freire, Ashraful Alam +6

For the first time, multi-task learning is proposed to improve the flexibility of NN-based equalizers in coherent systems. A "single" NN-based equalizer improves Q-factor by up to…

eess.SP2022★ 23 cited

Implementing Neural Network-Based Equalizers in a Coherent Optical Transmission System Using Field-Programmable Gate Arrays

Pedro J. Freire, Sasipim Srivallapanondh, Michael Anderson +9

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 t…

eess.SP2022★ 58 cited

Reducing Computational Complexity of Neural Networks in Optical Channel Equalization: From Concepts to Implementation

Pedro J. Freire, Antonio Napoli, Diego Arguello Ron +7

In this paper, a new methodology is proposed that allows for the low-complexity development of neural network (NN) based equalizers for the mitigation of impairments in high-speed…

eess.SP2021★ 8 cited

Performance versus Complexity Study of Neural Network Equalizers in Coherent Optical Systems

Pedro J. Freire, Yevhenii Osadchuk, Bernhard Spinnler +5

We present the results of the comparative analysis of the performance versus complexity for several types of artificial neural networks (NNs) used for nonlinear channel equalizatio…

physics.med-ph1999

Modelling a Parasystolic Rhythm in a Heart-Transplant Patient

M. Costa, I. R. Pimentel, T. Santiago +3

A parasystole from a heart-transplant patient is analysed using a beat-to-beat RR interval time series obtained from an electrocardiogram (ECG). The dysrhythmia, resulting from the…