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  1/2017 - 3

 HIGHLY CITED PAPER 

Adaptive Neuro-Fuzzy Based Gain Controller for Erbium-Doped Fiber Amplifiers

YUCEL, M. See more information about YUCEL, M. on SCOPUS See more information about YUCEL, M. on IEEExplore See more information about YUCEL, M. on Web of Science, CELEBI, F. V. See more information about  CELEBI, F. V. on SCOPUS See more information about  CELEBI, F. V. on SCOPUS See more information about CELEBI, F. V. on Web of Science, TORUN, M. See more information about  TORUN, M. on SCOPUS See more information about  TORUN, M. on SCOPUS See more information about TORUN, M. on Web of Science, GOKTAS, H. H. See more information about GOKTAS, H. H. on SCOPUS See more information about GOKTAS, H. H. on SCOPUS See more information about GOKTAS, H. H. on Web of Science
 
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Download PDF pdficon (1,245 KB) | Citation | Downloads: 976 | Views: 4,474

Author keywords
fuzzy neural networks, adaptive control, gain control, power control, erbium-doped fiber amplifiers

References keywords
fuzzy(22), optical(16), gain(16), edfa(11), celebi(10), systems(9), inference(9), control(9), anfis(9), adaptive(9)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2017-02-28
Volume 17, Issue 1, Year 2017, On page(s): 15 - 20
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.01003
Web of Science Accession Number: 000396335900003
SCOPUS ID: 85014152564

Abstract
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Full text preview
Erbium-doped fiber amplifiers (EDFA) must have a flat gain profile which is a very important parameter such as wavelength division multiplexing (WDM) and dense WDM (DWDM) applications for long-haul optical communication systems and networks. For this reason, it is crucial to hold a stable signal power per optical channel. For the purpose of overcoming performance decline of optical networks and long-haul optical systems, the gain of the EDFA must be controlled for it to be fixed at a high speed. In this study, due to the signal power attenuation in long-haul fiber optic communication systems and non-equal signal amplification in each channel, an automatic gain controller (AGC) is designed based on the adaptive neuro-fuzzy inference system (ANFIS) for EDFAs. The intelligent gain controller is implemented and the performance of this new electronic control method is demonstrated. The proposed ANFIS-based AGC-EDFA uses the experimental dataset to produce the ANFIS-based sets and the rule base. Laser diode currents are predicted within the accuracy rating over 98 percent with the proposed ANFIS-based system. Upon comparing ANFIS-based AGC-EDFA and experimental results, they were found to be very close and compatible.


References | Cited By  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 30,314 TCR
SCOPUS® Citations for all references: 38,349 TCR

Web of Science® Average Citations per reference: 572 ACR
SCOPUS® Average Citations per reference: 724 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

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