A new efficient LMS adaptive filtering algorithm

Sau Gee Chen; Yung An Kao; Kwung Yee Tsai

doi:10.1109/82.494387

A new efficient LMS adaptive filtering algorithm

Sau Gee Chen^*, Yung An Kao, Kwung Yee Tsai

^*Corresponding author for this work

National Yang Ming Chiao Tung University

Research output: Contribution to journal › Journal Article › peer-review

14 Scopus citations

Abstract

A new efficient LMS adaptive filtering algorithm is proposed. The algorithm has comparable performance to that of the direct-form LMS algorithm (DLMS), while costs N/2 - 1 fewer multiplications at the expense of N/2 + 5 more additions than the DLMS algorithm, where A is the number of filter taps. The new algorithm has one more parameter adaptation than the DLMS algorithm. Further, the algorithm was combined with sign LMS algorithm (SA), signed régresser algorithm (SRA) and zero forcing (ZFA) algorithm for more complexity reduction. Simulation results showed that the new combined algorithms converge as fast as the direct-form SA, SRA and ZFA algorithms, meanwhile still maintain comparable performances.

Original language	English
Pages (from-to)	372-378
Number of pages	7
Journal	IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing
Volume	43
Issue number	5
DOIs	https://doi.org/10.1109/82.494387
State	Published - 1996
Externally published	Yes

Access to Document

10.1109/82.494387

Cite this

@article{bb5826ab9388446c859579272ed6ff45,

title = "A new efficient LMS adaptive filtering algorithm",

abstract = "A new efficient LMS adaptive filtering algorithm is proposed. The algorithm has comparable performance to that of the direct-form LMS algorithm (DLMS), while costs N/2 - 1 fewer multiplications at the expense of N/2 + 5 more additions than the DLMS algorithm, where A is the number of filter taps. The new algorithm has one more parameter adaptation than the DLMS algorithm. Further, the algorithm was combined with sign LMS algorithm (SA), signed r{\'e}gresser algorithm (SRA) and zero forcing (ZFA) algorithm for more complexity reduction. Simulation results showed that the new combined algorithms converge as fast as the direct-form SA, SRA and ZFA algorithms, meanwhile still maintain comparable performances.",

author = "Chen, {Sau Gee} and Kao, {Yung An} and Tsai, {Kwung Yee}",

year = "1996",

doi = "10.1109/82.494387",

language = "英语",

volume = "43",

pages = "372--378",

journal = "IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing",

issn = "1057-7130",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "5",

}

TY - JOUR

T1 - A new efficient LMS adaptive filtering algorithm

AU - Chen, Sau Gee

AU - Kao, Yung An

AU - Tsai, Kwung Yee

PY - 1996

Y1 - 1996

N2 - A new efficient LMS adaptive filtering algorithm is proposed. The algorithm has comparable performance to that of the direct-form LMS algorithm (DLMS), while costs N/2 - 1 fewer multiplications at the expense of N/2 + 5 more additions than the DLMS algorithm, where A is the number of filter taps. The new algorithm has one more parameter adaptation than the DLMS algorithm. Further, the algorithm was combined with sign LMS algorithm (SA), signed régresser algorithm (SRA) and zero forcing (ZFA) algorithm for more complexity reduction. Simulation results showed that the new combined algorithms converge as fast as the direct-form SA, SRA and ZFA algorithms, meanwhile still maintain comparable performances.

AB - A new efficient LMS adaptive filtering algorithm is proposed. The algorithm has comparable performance to that of the direct-form LMS algorithm (DLMS), while costs N/2 - 1 fewer multiplications at the expense of N/2 + 5 more additions than the DLMS algorithm, where A is the number of filter taps. The new algorithm has one more parameter adaptation than the DLMS algorithm. Further, the algorithm was combined with sign LMS algorithm (SA), signed régresser algorithm (SRA) and zero forcing (ZFA) algorithm for more complexity reduction. Simulation results showed that the new combined algorithms converge as fast as the direct-form SA, SRA and ZFA algorithms, meanwhile still maintain comparable performances.

UR - http://www.scopus.com/inward/record.url?scp=0030143448&partnerID=8YFLogxK

U2 - 10.1109/82.494387

DO - 10.1109/82.494387

M3 - 文章

AN - SCOPUS:0030143448

SN - 1057-7130

VL - 43

SP - 372

EP - 378

JO - IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing

JF - IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing

IS - 5

ER -

A new efficient LMS adaptive filtering algorithm

Abstract

Access to Document

Other files and links

Fingerprint

Cite this