{"title":"一种新的二维块最小均方自适应算法","authors":"S. Attallah, M. Najim","doi":"10.5281/ZENODO.36070","DOIUrl":null,"url":null,"abstract":"In this paper, a new 2-D block LMS algorithm is presented. This algorithm, which is an exact mathematical formulation of classical 2-D LMS algorithms, presents the advantage of preserving a good convergence as the block size increases. The reduction in the computational complexity is achieved by exploiting the redundancy between successive computations, rather than using disjoint or partially overlapping windows. The latter are known to degrade the convergence when the block size is large.","PeriodicalId":282153,"journal":{"name":"1996 8th European Signal Processing Conference (EUSIPCO 1996)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new two-dimensional block least mean squares adaptive algorithm\",\"authors\":\"S. Attallah, M. Najim\",\"doi\":\"10.5281/ZENODO.36070\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a new 2-D block LMS algorithm is presented. This algorithm, which is an exact mathematical formulation of classical 2-D LMS algorithms, presents the advantage of preserving a good convergence as the block size increases. The reduction in the computational complexity is achieved by exploiting the redundancy between successive computations, rather than using disjoint or partially overlapping windows. The latter are known to degrade the convergence when the block size is large.\",\"PeriodicalId\":282153,\"journal\":{\"name\":\"1996 8th European Signal Processing Conference (EUSIPCO 1996)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1996 8th European Signal Processing Conference (EUSIPCO 1996)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5281/ZENODO.36070\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1996 8th European Signal Processing Conference (EUSIPCO 1996)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5281/ZENODO.36070","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new two-dimensional block least mean squares adaptive algorithm
In this paper, a new 2-D block LMS algorithm is presented. This algorithm, which is an exact mathematical formulation of classical 2-D LMS algorithms, presents the advantage of preserving a good convergence as the block size increases. The reduction in the computational complexity is achieved by exploiting the redundancy between successive computations, rather than using disjoint or partially overlapping windows. The latter are known to degrade the convergence when the block size is large.