{"title":"Convergence analysis of threshold-based sparse NLMS algorithm","authors":"A. Al-Hassan, A. I. Sulyman, A. Alsanie","doi":"10.1109/IEEEGCC.2013.6705780","DOIUrl":null,"url":null,"abstract":"In this paper we present a threshold-based sparse NLMS algorithm. The proposed algorithm uses an energy threshold criterion to detect tap sparseness and update the active coefficients accordingly. The propsed algorithm is simple to implement, and our simulation results shows that it has better estimation performance in terms of convergence speed and MSE than the standard NLMS algorithm.","PeriodicalId":316751,"journal":{"name":"2013 7th IEEE GCC Conference and Exhibition (GCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 7th IEEE GCC Conference and Exhibition (GCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEEGCC.2013.6705780","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract
In this paper we present a threshold-based sparse NLMS algorithm. The proposed algorithm uses an energy threshold criterion to detect tap sparseness and update the active coefficients accordingly. The propsed algorithm is simple to implement, and our simulation results shows that it has better estimation performance in terms of convergence speed and MSE than the standard NLMS algorithm.
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