An improverd variable step size LMS adaptive filtering algorithm

LMS (least mean square) algorithm is widely used due to its simple and stable performance. As is well known, there is an inherent conflict between the convergence rate and steady-state misadjustment, which can be overcome through the adjustment of size factor. The paper has analyzed some LMS algorit...

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Published in2009 IEEE Youth Conference on Information, Computing and Telecommunication pp. 495 - 497
Main Authors Li PingPing, Pei TengDa, Pei BingNan, Hu LiJun
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2009
Subjects
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ISBN1424450748
9781424450749
DOI10.1109/YCICT.2009.5382451

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Abstract LMS (least mean square) algorithm is widely used due to its simple and stable performance. As is well known, there is an inherent conflict between the convergence rate and steady-state misadjustment, which can be overcome through the adjustment of size factor. The paper has analyzed some LMS algorithms that already existed and a new improved variable step-size LMS algorithm is presented. The computer simulation results are consistent with the theoretic analysis, Which show that the algorithm not only has a faster convergence rate, but also has a smaller steady-state error.
AbstractList LMS (least mean square) algorithm is widely used due to its simple and stable performance. As is well known, there is an inherent conflict between the convergence rate and steady-state misadjustment, which can be overcome through the adjustment of size factor. The paper has analyzed some LMS algorithms that already existed and a new improved variable step-size LMS algorithm is presented. The computer simulation results are consistent with the theoretic analysis, Which show that the algorithm not only has a faster convergence rate, but also has a smaller steady-state error.
Author Pei BingNan
Li PingPing
Hu LiJun
Pei TengDa
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  surname: Hu LiJun
  fullname: Hu LiJun
  organization: 92819 Unit, PLA Marine, Dalian, China
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Snippet LMS (least mean square) algorithm is widely used due to its simple and stable performance. As is well known, there is an inherent conflict between the...
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StartPage 495
SubjectTerms Adaptive filters
Algorithm design and analysis
Computer simulation
Convergence
convergence rate
Educational institutions
Equations
Error correction
Filtering algorithms
Least squares approximation
LMS algorithm
Steady-state
steady-state error
variable step-size
Title An improverd variable step size LMS adaptive filtering algorithm
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