Euclidean direction search algorithm for adaptive filtering

Guo Fang Xu; Tamal Bose; Jim Schroeder

Euclidean direction search algorithm for adaptive filtering

Guo Fang Xu, Tamal Bose, Jim Schroeder

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A new least-squares adaptive algorithm, called the Euclidean Direction Search (EDS) algorithm is investigated for applications in fast adaptive filtering. Based on mathematical analysis and computer simulations, the proposed algorithm is shown to be very efficient for adaptive filtering applications such as noise cancellation and channel equalization. The algorithm features an O(N) computational complexity, fast convergence, improved numerical stability and least-squares optimal solution. Its convergence rate is comparable to that of the RLS but at a much lower computational cost.

Original language	English (US)
Title of host publication	Proceedings - IEEE International Symposium on Circuits and Systems
Publisher	IEEE
Pages	III-146 - III-149
ISBN (Print)	0780354710
State	Published - 1999
Externally published	Yes
Event	Proceedings of the 1999 IEEE International Symposium on Circuits and Systems, ISCAS '99 - Orlando, FL, USA Duration: May 30 1999 → Jun 2 1999

Publication series

Name	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	3
ISSN (Print)	0271-4310

Other

Other	Proceedings of the 1999 IEEE International Symposium on Circuits and Systems, ISCAS '99
City	Orlando, FL, USA
Period	5/30/99 → 6/2/99

ASJC Scopus subject areas

Electrical and Electronic Engineering

Cite this

Euclidean direction search algorithm for adaptive filtering. / Xu, Guo Fang; Bose, Tamal; Schroeder, Jim.
Proceedings - IEEE International Symposium on Circuits and Systems. IEEE, 1999. p. III-146 - III-149 (Proceedings - IEEE International Symposium on Circuits and Systems; Vol. 3).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Xu, GF, Bose, T & Schroeder, J 1999, Euclidean direction search algorithm for adaptive filtering. in Proceedings - IEEE International Symposium on Circuits and Systems. Proceedings - IEEE International Symposium on Circuits and Systems, vol. 3, IEEE, pp. III-146 - III-149, Proceedings of the 1999 IEEE International Symposium on Circuits and Systems, ISCAS '99, Orlando, FL, USA, 5/30/99.

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abstract = "A new least-squares adaptive algorithm, called the Euclidean Direction Search (EDS) algorithm is investigated for applications in fast adaptive filtering. Based on mathematical analysis and computer simulations, the proposed algorithm is shown to be very efficient for adaptive filtering applications such as noise cancellation and channel equalization. The algorithm features an O(N) computational complexity, fast convergence, improved numerical stability and least-squares optimal solution. Its convergence rate is comparable to that of the RLS but at a much lower computational cost.",

author = "Xu, {Guo Fang} and Tamal Bose and Jim Schroeder",

year = "1999",

language = "English (US)",

isbn = "0780354710",

series = "Proceedings - IEEE International Symposium on Circuits and Systems",

publisher = "IEEE",

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note = "Proceedings of the 1999 IEEE International Symposium on Circuits and Systems, ISCAS '99 ; Conference date: 30-05-1999 Through 02-06-1999",

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AU - Bose, Tamal

AU - Schroeder, Jim

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N2 - A new least-squares adaptive algorithm, called the Euclidean Direction Search (EDS) algorithm is investigated for applications in fast adaptive filtering. Based on mathematical analysis and computer simulations, the proposed algorithm is shown to be very efficient for adaptive filtering applications such as noise cancellation and channel equalization. The algorithm features an O(N) computational complexity, fast convergence, improved numerical stability and least-squares optimal solution. Its convergence rate is comparable to that of the RLS but at a much lower computational cost.

AB - A new least-squares adaptive algorithm, called the Euclidean Direction Search (EDS) algorithm is investigated for applications in fast adaptive filtering. Based on mathematical analysis and computer simulations, the proposed algorithm is shown to be very efficient for adaptive filtering applications such as noise cancellation and channel equalization. The algorithm features an O(N) computational complexity, fast convergence, improved numerical stability and least-squares optimal solution. Its convergence rate is comparable to that of the RLS but at a much lower computational cost.

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M3 - Conference contribution

AN - SCOPUS:0032691673

SN - 0780354710

T3 - Proceedings - IEEE International Symposium on Circuits and Systems

SP - III-146 - III-149

BT - Proceedings - IEEE International Symposium on Circuits and Systems

PB - IEEE

T2 - Proceedings of the 1999 IEEE International Symposium on Circuits and Systems, ISCAS '99

Y2 - 30 May 1999 through 2 June 1999

ER -

Euclidean direction search algorithm for adaptive filtering

Abstract

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ASJC Scopus subject areas

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