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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Alves, T. M. F., Piedade, D., Brandão, T., Rebola, J. L. & Cartaxo, A. V. T. (2023). On the use of Feedforward Neural Networks to improve the intercore crosstalk tolerance in self-coherent MCF systems. In Jaworski, M., and Marciniak, M. (Ed.), 2023 23rd International Conference on Transparent Optical Networks (ICTON). Bucharest, Romania: IEEE.
Exportar Referência (IEEE)
T. M. Alves et al.,  "On the use of Feedforward Neural Networks to improve the intercore crosstalk tolerance in self-coherent MCF systems", in 2023 23rd Int. Conf. on Transparent Optical Networks (ICTON), Jaworski, M., and Marciniak, M., Ed., Bucharest, Romania, IEEE, 2023
Exportar BibTeX
@inproceedings{alves2023_1730794601504,
	author = "Alves, T. M. F. and Piedade, D. and Brandão, T. and Rebola, J. L. and Cartaxo, A. V. T.",
	title = "On the use of Feedforward Neural Networks to improve the intercore crosstalk tolerance in self-coherent MCF systems",
	booktitle = "2023 23rd International Conference on Transparent Optical Networks (ICTON)",
	year = "2023",
	editor = "Jaworski, M., and Marciniak, M.",
	volume = "",
	number = "",
	series = "",
	doi = "10.1109/ICTON59386.2023.10207228",
	publisher = "IEEE",
	address = "Bucharest, Romania",
	organization = "",
	url = "https://ieeexplore.ieee.org/xpl/conhome/10207167/proceeding"
}
Exportar RIS
TY  - CPAPER
TI  - On the use of Feedforward Neural Networks to improve the intercore crosstalk tolerance in self-coherent MCF systems
T2  - 2023 23rd International Conference on Transparent Optical Networks (ICTON)
AU  - Alves, T. M. F.
AU  - Piedade, D.
AU  - Brandão, T.
AU  - Rebola, J. L.
AU  - Cartaxo, A. V. T.
PY  - 2023
SN  - 2162-7339
DO  - 10.1109/ICTON59386.2023.10207228
CY  - Bucharest, Romania
UR  - https://ieeexplore.ieee.org/xpl/conhome/10207167/proceeding
AB  - An artificial neural network is investigated to improve the performance of self-coherent weakly-coupled multicore fibre (WC-MCF) systems. Particularly, a feedforward neural network (FNN) is proposed to mitigate the performance degradation induced by the random variation of the intercore crosstalk along time in 64 Gbaud quadrature amplitude modulation WC-MCF systems. A product between the intercore skew and the symbol rate much lower than one and a self-coherent receiver based on Kramers-Kronig technique, are considered. Compared with the reference system without neural networks, an improvement of the tolerable ICXT level close to 12 dB is achieved with the proposed shallow FNN.
ER  -