Automatic Identification of Impairments Using Support Vector Machine Pattern Classification on Eye Diagrams

Author

Skoog, Ronald A. ; Banwell, Thomas C. ; Gannett, Joel W. ; Habiby, Sarry F. ; Pang, Marcus ; Rauch, Michael E. ; Toliver, Paul

Author_Institution

Appl. Res., Telcordia Technol., Red Bank, NJ

Volume

18

Issue

22

fYear

2006

Firstpage

2398

Lastpage

2400

Abstract

We have demonstrated powerful new techniques for identifying the optical impairments causing the degradation of an optical channel. We use machine learning and pattern classification techniques on eye diagrams to identify the optical impairments. These capabilities can enable the development of low-cost optical performance monitors having significant diagnostic capabilities

Keywords

learning (artificial intelligence); optical fibre communication; pattern classification; support vector machines; telecommunication channels; telecommunication computing; eye diagrams; machine learning; optical impairment identification; pattern classification; support vector machine; Degradation; Machine learning; Monitoring; Optical character recognition software; Optical computing; Pattern classification; Signal analysis; Signal processing; Support vector machine classification; Support vector machines; Machine learning; optical performance monitoring (OPM); pattern recognition;

fLanguage

English

Journal_Title

Photonics Technology Letters, IEEE

Publisher

ieee

ISSN

1041-1135

Type

jour

DOI

10.1109/LPT.2006.886146

Filename

4012069