An Improved Proportionate Normalized Least Mean Square Algorithm for Sparse Impulse Response Identification

In this paper after analyzing the adaptation process of the proportionate normalized least mean square （PNLMS） algorithm, a statistical model is obtained to describe the convergence process of each adaptive filter coefficient. Inspired by this result, a modified PNLMS algorithm based on precise magn...

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Published inShanghai jiao tong da xue xue bao Vol. 18; no. 6; pp. 742 - 748
Main Author 文昊翔 赖晓翰 陈隆道 蔡忠法
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2013
Subjects
Architecture
Computer Science
Electrical Engineering
Engineering
Life Sciences
Materials Science
TM 714
adaptive algorithm
proportionate step-size
echo cancellation (EC)
proportionate normalized least mean square (PNLMS) algorithm
sparse impulse response
Online AccessGet full text
ISSN1007-1172
1995-8188
DOI10.1007/s12204-013-1460-8

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Summary:In this paper after analyzing the adaptation process of the proportionate normalized least mean square （PNLMS） algorithm, a statistical model is obtained to describe the convergence process of each adaptive filter coefficient. Inspired by this result, a modified PNLMS algorithm based on precise magnitude estimate is proposed. The simulation results indicate that in contrast to the traditional PNLMS algorithm, the proposed algorithm achieves faster convergence speed in the initial convergence state and lower misalignment in the stead stage with much less computational complexity.
Bibliography:WEN Hao-xiang, LAI Xiao-han, CHEN Long-dao, CAI Zhong-fa（College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China）
31-1943/U
In this paper after analyzing the adaptation process of the proportionate normalized least mean square （PNLMS） algorithm, a statistical model is obtained to describe the convergence process of each adaptive filter coefficient. Inspired by this result, a modified PNLMS algorithm based on precise magnitude estimate is proposed. The simulation results indicate that in contrast to the traditional PNLMS algorithm, the proposed algorithm achieves faster convergence speed in the initial convergence state and lower misalignment in the stead stage with much less computational complexity.
adaptive algorithm, echo cancellation （EC）, proportionate normalized least mean square （PNLMS）algorithm, proportionate step-size, sparse impulse response
ISSN:1007-1172
1995-8188
DOI:10.1007/s12204-013-1460-8