Mapping EDFA Noise Figure and Gain Flatness Over the Power Mask Using Neural Networks.

Autor:	Bastos-Filho, Carmelo J. A., Barboza, Erick de A., Martins-Filho, Joaquim F., de Moura, Uiara C., de Oliveira, Juliano R. F.
Předmět:	OPTICAL amplifiers OPTICAL communications ERBIUM DOPED semiconductors ARTIFICIAL neural networks MULTILAYER perceptrons REGRESSION analysis MISSING data (Statistics)
Zdroj:	Journal of Microwaves, Optoelectronics & Electromagnetic Applications; Jul2013 SI-2, Vol. 12, p128-139, 12p
Abstrakt:	Optical Amplifiers play an important hole in reconfigurable optical communications networks. The device characterization within the dynamic operational range is crucial for the proper deployment and usage of such devices. In general, one needs to measure a certain number of operation points to complete the characterization. In spite of this, there is a lot of missing data for some operational deployment cases. We show that one can use simple neural networks to execute a regression task and obtain a continuous characterization curve of Gain Flatness and Noise Figure performance, along the entire Amplifier Power Mask. This regression can be made using a lower number of points than usual. We obtained estimated errors lower than 0.1 dB for Gain Flatness and Noise Figure over the entire operational range. [ABSTRACT FROM AUTHOR]
Databáze:	Complementary Index
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