{"title":"Bi-dimensional Neural Equalizer Applied to Optical Receiver","authors":"Tiago F. B. de Sousa, Marcelo A. C. Fernandes","doi":"10.1109/BRICS-CCI-CBIC.2013.17","DOIUrl":null,"url":null,"abstract":"Optical fibers are commonly used in communications today, mainly because that the data transmission rates of those systems are faster than those in any other digital communication system. Despite this great advantage, some problems prevent the full use of optical connection: by increasing transmission rates over longer distances, the data is affected by non-linear inter-symbol interference caused by the dispersion phenomena in the fiber. Adaptive equalizers can be used to compensate for the effects caused by channel non-linear responses, restoring the originally transmitted signal. The present study discusses a proposal based on artificial neural networks, a neural equalizer. The proposal is validated through a simulated optic channel and the comparison with other adaptive equalization techniques.","PeriodicalId":306195,"journal":{"name":"2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BRICS-CCI-CBIC.2013.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Optical fibers are commonly used in communications today, mainly because that the data transmission rates of those systems are faster than those in any other digital communication system. Despite this great advantage, some problems prevent the full use of optical connection: by increasing transmission rates over longer distances, the data is affected by non-linear inter-symbol interference caused by the dispersion phenomena in the fiber. Adaptive equalizers can be used to compensate for the effects caused by channel non-linear responses, restoring the originally transmitted signal. The present study discusses a proposal based on artificial neural networks, a neural equalizer. The proposal is validated through a simulated optic channel and the comparison with other adaptive equalization techniques.