ScholarLens Back to search
2006•Dianzi xuebaoRequires access

A New Variable Step Size LMS Adaptive Filtering Algorithm

Qiang Wang

Open publisher page 8 citations

Abstract

By building a nonlinear function relationship between μ and the error signal,this paper presents a novel variable step size LMS(Least Mean Square)adaptive filtering algorithm.The step size of this algorithm increases automaticly at the beginning of this algorithm or when unknown system is changing with time,and it would be smaller during the steady state.This algorithm avoid the shortage of changing step size of SVSLMS,variable step size LMS based on Sigmoid function,in the process of the adaptive steady state.The performance of this paper algorithm is better than that of SVSLMS with the theoretical analysis and computer simulations.

About this research paper

What this paper is about

By building a nonlinear function relationship between μ and the error signal,this paper presents a novel variable step size LMS(Least Mean Square)adaptive filtering algorithm.The step size of this algorithm increases automaticly at the beginning of this algorithm or when unknown system is changing with time,and it would be smaller during the steady state.This algorithm avoid the shortage of changing step size of SVSLMS,variable step size LMS based on Sigmoid function,in the process of the adaptive steady state.The performance of this paper algorithm is better than that of SVSLMS with the theoretical analysis and computer simulations.

Why it matters

OpenAlex reports 8 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

By building a nonlinear function relationship between μ and the error signal,this paper presents a novel variable step size LMS(Least Mean Square)adaptive filtering algorithm.The step size of this algorithm increases automaticly at the beginning of this algorithm or when unknown system is changing with time,and it would be smaller during the steady state.This algorithm avoid the shortage of changing step size of SVSLMS,variable step size LMS based on Sigmoid function,in the process of the adaptive steady state.The performance of this paper algorithm is better than that of SVSLMS with the theoretical analysis and computer simulations.

Key concepts: Least mean squares filter, Sigmoid function, Adaptive filter, Variable (mathematics), Algorithm, Adaptive algorithm, Steady state (chemistry), Nonlinear system

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
A New Variable Step Size LMS Adaptive Filtering Algorithm — Research Paper | ScholarLens