Euclidean direction search algorithm for adaptive filtering

Guo Fang Xu, Tamal Bose, Jim Schroeder

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

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 languageEnglish (US)
Title of host publicationProceedings - IEEE International Symposium on Circuits and Systems
PublisherIEEE
PagesIII-146 - III-149
ISBN (Print)0780354710
StatePublished - Jan 1 1999
Externally publishedYes
EventProceedings of the 1999 IEEE International Symposium on Circuits and Systems, ISCAS '99 - Orlando, FL, USA
Duration: May 30 1999Jun 2 1999

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume3
ISSN (Print)0271-4310

Other

OtherProceedings of the 1999 IEEE International Symposium on Circuits and Systems, ISCAS '99
CityOrlando, FL, USA
Period5/30/996/2/99

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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