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2011•Computer Engineering and Applications JournalRequires access

Improved adaptive LMS algorithm

Lijun Hu

Open publisher page 1 citations

Abstract

LMS(Least Mean Square) algorithm is widely used due to its simple and stable performance.But there is an inherent conflict between the convergence rate and steady-state misadjustment,which can be overcome through the adjustment of size factor.A new improved LMS algorithm is presented according to the analysis of some variable step size algorithms.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.

About this research paper

What this paper is about

LMS(Least Mean Square) algorithm is widely used due to its simple and stable performance.But there is an inherent conflict between the convergence rate and steady-state misadjustment,which can be overcome through the adjustment of size factor.A new improved LMS algorithm is presented according to the analysis of some variable step size algorithms.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.

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Available abstract

LMS(Least Mean Square) algorithm is widely used due to its simple and stable performance.But there is an inherent conflict between the convergence rate and steady-state misadjustment,which can be overcome through the adjustment of size factor.A new improved LMS algorithm is presented according to the analysis of some variable step size algorithms.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.

Key concepts: Least mean squares filter, Convergence (economics), Rate of convergence, Steady state (chemistry), Algorithm, Adaptive filter, Computer science, Variable (mathematics)

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