The Euclidean Direction Search algorithm in adaptive filtering

Tamal Bose, G. F. Xu

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

A new class of least-squares algorithms is presented for adaptive filtering. The idea is to use a fixed set of directions and perform line search with one direction at a time in a cyclic fashion. These algorithms are called Euclidean Direction Search (EDS) algorithms. The fast version of this class is called the Fast-EDS or FEDS algorithm. It is shown to have O(N) computational complexity and a convergence rate comparable to that of the RLS algorithm. Computer simulations are presented to illustrate the performance of the new algorithm.

Original languageEnglish (US)
Pages (from-to)532-539
Number of pages8
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE85-A
Issue number3
StatePublished - Mar 2002
Externally publishedYes

Fingerprint

Adaptive Filtering
Adaptive filtering
Search Algorithm
Euclidean
Least Square Algorithm
Line Search
Convergence Rate
Computational Complexity
Computer Simulation
Computational complexity
Computer simulation
Class

Keywords

  • Adaptive filters
  • Channel equalizer
  • Euclidean direction search
  • Image restoration
  • Least squares

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Hardware and Architecture
  • Information Systems

Cite this

The Euclidean Direction Search algorithm in adaptive filtering. / Bose, Tamal; Xu, G. F.

In: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol. E85-A, No. 3, 03.2002, p. 532-539.

Research output: Contribution to journalArticle

@article{a7d77f7140ee49fb8a0f20e50224b50c,
title = "The Euclidean Direction Search algorithm in adaptive filtering",
abstract = "A new class of least-squares algorithms is presented for adaptive filtering. The idea is to use a fixed set of directions and perform line search with one direction at a time in a cyclic fashion. These algorithms are called Euclidean Direction Search (EDS) algorithms. The fast version of this class is called the Fast-EDS or FEDS algorithm. It is shown to have O(N) computational complexity and a convergence rate comparable to that of the RLS algorithm. Computer simulations are presented to illustrate the performance of the new algorithm.",
keywords = "Adaptive filters, Channel equalizer, Euclidean direction search, Image restoration, Least squares",
author = "Tamal Bose and Xu, {G. F.}",
year = "2002",
month = "3",
language = "English (US)",
volume = "E85-A",
pages = "532--539",
journal = "IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences",
issn = "0916-8508",
publisher = "Maruzen Co., Ltd/Maruzen Kabushikikaisha",
number = "3",

}

TY - JOUR

T1 - The Euclidean Direction Search algorithm in adaptive filtering

AU - Bose, Tamal

AU - Xu, G. F.

PY - 2002/3

Y1 - 2002/3

N2 - A new class of least-squares algorithms is presented for adaptive filtering. The idea is to use a fixed set of directions and perform line search with one direction at a time in a cyclic fashion. These algorithms are called Euclidean Direction Search (EDS) algorithms. The fast version of this class is called the Fast-EDS or FEDS algorithm. It is shown to have O(N) computational complexity and a convergence rate comparable to that of the RLS algorithm. Computer simulations are presented to illustrate the performance of the new algorithm.

AB - A new class of least-squares algorithms is presented for adaptive filtering. The idea is to use a fixed set of directions and perform line search with one direction at a time in a cyclic fashion. These algorithms are called Euclidean Direction Search (EDS) algorithms. The fast version of this class is called the Fast-EDS or FEDS algorithm. It is shown to have O(N) computational complexity and a convergence rate comparable to that of the RLS algorithm. Computer simulations are presented to illustrate the performance of the new algorithm.

KW - Adaptive filters

KW - Channel equalizer

KW - Euclidean direction search

KW - Image restoration

KW - Least squares

UR - http://www.scopus.com/inward/record.url?scp=0036522870&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0036522870&partnerID=8YFLogxK

M3 - Article

VL - E85-A

SP - 532

EP - 539

JO - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

JF - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

SN - 0916-8508

IS - 3

ER -