Modular neural networks for quality of transmission prediction in low-margin optical networks
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Industrial and Manufacturing Engineering,Software
Link
https://link.springer.com/content/pdf/10.1007/s10845-020-01576-z.pdf
Reference32 articles.
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3. Bosco, G., Curri, V., Carena, A., Poggiolini, P., & Forghieri, F. (2011). On the performance of Nyquist-WDM terabit superchannels based on PM-BPSK, PM-QPSK, PM-8QAM or PM-16QAM subcarriers. Journal of Lightwave Technology, 29(1), 53–61.
4. Caballero, F., Ives, D., Zhuge, Q., O’Sullivan, M., & Savory, S. J. (2018). Joint estimation of linear and non-linear signal-to-noise ratio based on neural networks. In Optical fiber communication conference (OFC), paper M2F.4.
5. Caflisch, R. (1998). Monte Carlo and quasi-Monte Carlo methods. Acta Numerica, 7, 1. https://doi.org/10.1017/s0962492900002804.
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