The Euclidean Direction Search Algorithm in Adaptive Filtering
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E85-A No.3 pp.532-539
- Publication Date
- 2002/03/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Special Section INVITED PAPER (Special Section on the Trend of Digital Signal Processing and Its Future Direction)
- Category
- Theories
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Tamal BOSE, Guo-Fang XU, "The Euclidean Direction Search Algorithm in Adaptive Filtering" in IEICE TRANSACTIONS on Fundamentals,
vol. E85-A, no. 3, pp. 532-539, March 2002, doi: .
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.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e85-a_3_532/_p
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@ARTICLE{e85-a_3_532,
author={Tamal BOSE, Guo-Fang XU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={The Euclidean Direction Search Algorithm in Adaptive Filtering},
year={2002},
volume={E85-A},
number={3},
pages={532-539},
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={},
doi={},
ISSN={},
month={March},}
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TY - JOUR
TI - The Euclidean Direction Search Algorithm in Adaptive Filtering
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 532
EP - 539
AU - Tamal BOSE
AU - Guo-Fang XU
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E85-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 2002
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.
ER -
English
