Title :
Robust, compact, and flexible neural model for a fiber Raman amplifier
Author :
Zhou, Junhe ; Chen, Jianping ; Li, Xinwan ; Wu, Guiling ; Wang, Yiping ; Jiang, Wenning
Author_Institution :
State Key Lab. on Fiber-Opt. Local Area Commun. Networks & Adv. Opt. Commun. Syst., Shanghai Jiao Tong Univ., China
fDate :
6/1/2006 12:00:00 AM
Abstract :
In this paper, a novel robust, compact, and flexible neural-network model for a fiber Raman amplifier (FRA) is presented. The model can be used in various applications with promising accuracy and low requirement for memory. Analytical expressions are derived in order to make the optimal pump-power configuration much easier, and the computational time is reduced dramatically in comparison with other gain-design methods in real-time pump-power adjustment. The calculated on-off gain spectrum and the noise figure using the proposed model agree well with the experimental results. The model has a potential value in simulation and pump-power dynamic control.
Keywords :
Raman lasers; neural nets; optical fibre amplifiers; optical pumping; Raman amplifier; fiber amplifier; gain-design methods; neural model; neural network; noise figure; on-off gain spectrum; pump-power configuration; pump-power dynamic control; Design optimization; Integral equations; Nonlinear equations; Optical fiber amplifiers; Optical fiber communication; Optical fibers; Robustness; Semiconductor optical amplifiers; Stimulated emission; US Department of Transportation; Neural network; Raman scattering;
Journal_Title :
Lightwave Technology, Journal of
DOI :
10.1109/JLT.2006.874602
