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2009•Microcomputer applicationsRequires access

A Improved LMS Type Algorithm Based on MVSSLMS

Dandan Wang

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Abstract

Following a brief discussion on traditional LMS and its improved algorithm,this paper presents a improved variable step size algorithm,which uses the estimation of the autocorrelation and means square error to adjust the step of adaptive algorithm.Computer simulation result verifies the improved algorithm has faster convergence rate than traditional LMS and MVSSLMS.

About this research paper

What this paper is about

Following a brief discussion on traditional LMS and its improved algorithm,this paper presents a improved variable step size algorithm,which uses the estimation of the autocorrelation and means square error to adjust the step of adaptive algorithm.Computer simulation result verifies the improved algorithm has faster convergence rate than traditional LMS and MVSSLMS.

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Key contribution

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Method / approach

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Main findings

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Available abstract

Following a brief discussion on traditional LMS and its improved algorithm,this paper presents a improved variable step size algorithm,which uses the estimation of the autocorrelation and means square error to adjust the step of adaptive algorithm.Computer simulation result verifies the improved algorithm has faster convergence rate than traditional LMS and MVSSLMS.

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

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