Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Pedro J. Freire"'
Autor:
Diego Argüello Ron, Pedro J. Freire, Jaroslaw E. Prilepsky, Morteza Kamalian-Kopae, Antonio Napoli, Sergei K. Turitsyn
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-14 (2022)
Abstract The deployment of artificial neural networks-based optical channel equalizers on edge-computing devices is critically important for the next generation of optical communication systems. However, this is still a highly challenging problem, ma
Externí odkaz:
https://doaj.org/article/c88a61f0e1294dcba115f065bf58947b
Autor:
Egor V. Sedov, Pedro J. Freire, Vladimir V. Seredin, Vladyslav A. Kolbasin, Morteza Kamalian-Kopae, Igor S. Chekhovskoy, Sergei K. Turitsyn, Jaroslaw E. Prilepsky
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
Abstract We combine the nonlinear Fourier transform (NFT) signal processing with machine learning methods for solving the direct spectral problem associated with the nonlinear Schrödinger equation. The latter is one of the core nonlinear science mod
Externí odkaz:
https://doaj.org/article/90fe5d2116484d4981a9d40767e509f4
Publikováno v:
Physiological Reports, Vol 7, Iss 6, Pp n/a-n/a (2019)
Abstract In vivo metabolic studies typically concern complex open systems. However, a closed system allows better assessment of the metabolic limits. Ischemic priapism (IP) constitutes a special model of the compartment syndrome that allows direct sa
Externí odkaz:
https://doaj.org/article/f4e19050026d4d64a2f2c8c107cbd7eb
Autor:
Pedro J. Freire, Sasipim Srivallapanondh, Michael Anderson, Bernhard Spinnler, Thomas Bex, Tobias A. Eriksson, Antonio Napoli, Wolfgang Schairer, Nelson Costa, Michaela Blott, Sergei K. Turitsyn, Jaroslaw E. Prilepsky
Publikováno v:
Arxiv
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 transmission systems. First, we present a realization pipeline showing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a28ef583132776259b51a45bbeb1eec1
https://doi.org/10.1109/jlt.2023.3272011
https://doi.org/10.1109/jlt.2023.3272011
Publikováno v:
IEEE Transactions on Communications. 70:7973-7988
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c38530b47ecf1ace830ca00904471760
https://doi.org/10.1109/tcomm.2022.3213284
https://doi.org/10.1109/tcomm.2022.3213284
Autor:
Pedro J. Freire, Antonio Napoli, Bernhard Spinnler, Nelson Costa, Sergei K. Turitsyn, Jaroslaw E. Prilepsky
Publikováno v:
IEEE Journal of Selected Topics in Quantum Electronics. 28:1-23
This paper performs a detailed, multi-faceted analysis of key challenges and common design caveats related to the development of efficient neural networks (NN) nonlinear channel equalizers in coherent optical communication systems. Our study aims to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bc6883ebf0db7cbb2dc2b70e031eca2e
https://doi.org/10.1109/jstqe.2022.3174268
https://doi.org/10.1109/jstqe.2022.3174268
Publikováno v:
Optical Fiber Communication Conference (OFC) 2023.
We investigated data augmentation to train neural networks (NNs) for soft-failure cause identification, demonstrating its impacts on NN complexity. Results indicate up to 68% reduction in the computational complexity of NN for each inference.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3bd563807a8bb5c2764982f8c4a78a80
https://doi.org/10.1364/ofc.2023.m3g.3
https://doi.org/10.1364/ofc.2023.m3g.3
Autor:
Bernhard Spinnler, Sergei K. Turitsyn, Jaroslaw E. Prilepsky, Yevhenii Osadchuk, Nelson Costa, Wolfgang Schairer, Pedro J. Freire, Antonio Napoli
Publikováno v:
Journal of Lightwave Technology
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 equalization in coherent optical communication systems. The comparison has been c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bc95619b0d13c32e725a6a20e765958d
https://doi.org/10.1109/jlt.2021.3096286
https://doi.org/10.1109/jlt.2021.3096286
Autor:
Pedro J. Freire, Antonio Napoli, Diego Arguello Ron, Bernhard Spinnler, Michael Anderson, Wolfgang Schairer, Thomas Bex, Nelson Costa, Sergei K. Turitsyn, Jaroslaw E. Prilepsky
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 coherent optical transmission systems. In this work, we provide a comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::14f574b621b3f635f73a1a3e0aba405e
http://arxiv.org/abs/2208.12866
http://arxiv.org/abs/2208.12866
