{"title":"不完全估计系统延迟的改进泄漏延迟LMS算法","authors":"Juan R. V. Lopez, O. J. Tobias, R. Seara","doi":"10.5281/ZENODO.40279","DOIUrl":null,"url":null,"abstract":"This paper proposes a modified leaky delayed least-mean-square (MLDLMS) algorithm, aiming to circumvent algorithm instability problems under imperfect system delay estimates. In addition, a model for the first and second moments of the algorithm is proposed. Such a model is obtained without invoking the independence theory and considering a slow adaptation condition. Numerical simulations corroborate the very good agreement between the results obtained with the Monte Carlo method and those from the proposed model for colored Gaussian inputs.","PeriodicalId":176384,"journal":{"name":"2007 15th European Signal Processing Conference","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Modified leaky delayed LMS algorithm for imperfect estimate system delay\",\"authors\":\"Juan R. V. Lopez, O. J. Tobias, R. Seara\",\"doi\":\"10.5281/ZENODO.40279\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a modified leaky delayed least-mean-square (MLDLMS) algorithm, aiming to circumvent algorithm instability problems under imperfect system delay estimates. In addition, a model for the first and second moments of the algorithm is proposed. Such a model is obtained without invoking the independence theory and considering a slow adaptation condition. Numerical simulations corroborate the very good agreement between the results obtained with the Monte Carlo method and those from the proposed model for colored Gaussian inputs.\",\"PeriodicalId\":176384,\"journal\":{\"name\":\"2007 15th European Signal Processing Conference\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 15th European Signal Processing Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5281/ZENODO.40279\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 15th European Signal Processing Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5281/ZENODO.40279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modified leaky delayed LMS algorithm for imperfect estimate system delay
This paper proposes a modified leaky delayed least-mean-square (MLDLMS) algorithm, aiming to circumvent algorithm instability problems under imperfect system delay estimates. In addition, a model for the first and second moments of the algorithm is proposed. Such a model is obtained without invoking the independence theory and considering a slow adaptation condition. Numerical simulations corroborate the very good agreement between the results obtained with the Monte Carlo method and those from the proposed model for colored Gaussian inputs.