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

Volume

24

Issue

6

fYear

2006

fDate

6/1/2006 12:00:00 AM

Firstpage

2362

Lastpage

2367

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;

fLanguage

English

Journal_Title

Lightwave Technology, Journal of

Publisher

ieee

ISSN

0733-8724

Type

jour

DOI

10.1109/JLT.2006.874602

Filename

1643794