R. G. Alves, M. R. Petraglia, J. A. Apolinário, P. Diniz
{"title":"RLS algorithm for a new subband adaptive structure with critical sampling","authors":"R. G. Alves, M. R. Petraglia, J. A. Apolinário, P. Diniz","doi":"10.1109/ITS.1998.718434","DOIUrl":null,"url":null,"abstract":"In a recent publication new family of adaptive structures with critical sampling of the subband signals, which yields exact modeling of FIR systems, was obtained. In this paper an algorithm based on the recursive least-squares (RLS) algorithm is derived for the updating of the adaptive coefficients of this new subband structure. An efficient implementation of the resulting structure is discussed, leading to computational complexity savings. Computer simulations illustrate the convergence behavior of the proposed algorithm.","PeriodicalId":205350,"journal":{"name":"ITS'98 Proceedings. SBT/IEEE International Telecommunications Symposium (Cat. No.98EX202)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ITS'98 Proceedings. SBT/IEEE International Telecommunications Symposium (Cat. No.98EX202)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITS.1998.718434","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
In a recent publication new family of adaptive structures with critical sampling of the subband signals, which yields exact modeling of FIR systems, was obtained. In this paper an algorithm based on the recursive least-squares (RLS) algorithm is derived for the updating of the adaptive coefficients of this new subband structure. An efficient implementation of the resulting structure is discussed, leading to computational complexity savings. Computer simulations illustrate the convergence behavior of the proposed algorithm.