{"title":"An approach for channel equalization using quasi type-2 fuzzy systems","authors":"Luis F. Albarracin, M. Melgarejo","doi":"10.1109/NAFIPS.2010.5548203","DOIUrl":null,"url":null,"abstract":"This article presents a simple approach for the equalization of a nonlinear time varying communication channel using a quasi type-2 fuzzy system. Basically, the Quasi-type 2 fuzzy equalizer is tuned by clustering the output of the channel as it is proposed in previous reported works for other fuzzy equalizers. The main difference is that the quasi type-2 fuzzy perspective permits to derive more design parameters from clustering. The proposed equalizer is compared with type one and interval type-2 equalizers. Although, simulation results show that the quasi type-2 fuzzy adaptive filter exhibits better performance for particular levels of uncertainty, it behaves similarly to the other equalizers in general terms.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2010.5548203","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
This article presents a simple approach for the equalization of a nonlinear time varying communication channel using a quasi type-2 fuzzy system. Basically, the Quasi-type 2 fuzzy equalizer is tuned by clustering the output of the channel as it is proposed in previous reported works for other fuzzy equalizers. The main difference is that the quasi type-2 fuzzy perspective permits to derive more design parameters from clustering. The proposed equalizer is compared with type one and interval type-2 equalizers. Although, simulation results show that the quasi type-2 fuzzy adaptive filter exhibits better performance for particular levels of uncertainty, it behaves similarly to the other equalizers in general terms.