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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 -