A Robust Recursive Least Square Algorithm against Impulsive Noise
Summary :
In this paper, we propose a robust adaptive algorithm for impulsive noise suppression. The perturbation of the input signal as well as the perturbation of the estimation error are restricted by M-estimation. The threshold used in M-estimation is obtained from the proposed adaptive variance estimation. Simulations show that the proposed algorithm is less vulnerable to the impulsive noise than the conventional algorithm.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E87-A No.9 pp.2463-2465
- Publication Date
- 2004/09/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- LETTER
- Category
- Digital Signal Processing
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Seong-Joon BAEK, Jinyoung KIM, Dae-Jin KIM, Dong-Soo HAR, Kiseon KIM, "A Robust Recursive Least Square Algorithm against Impulsive Noise" in IEICE TRANSACTIONS on Fundamentals,
vol. E87-A, no. 9, pp. 2463-2465, September 2004, doi: .
Abstract: In this paper, we propose a robust adaptive algorithm for impulsive noise suppression. The perturbation of the input signal as well as the perturbation of the estimation error are restricted by M-estimation. The threshold used in M-estimation is obtained from the proposed adaptive variance estimation. Simulations show that the proposed algorithm is less vulnerable to the impulsive noise than the conventional algorithm.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e87-a_9_2463/_p
Copy
@ARTICLE{e87-a_9_2463,
author={Seong-Joon BAEK, Jinyoung KIM, Dae-Jin KIM, Dong-Soo HAR, Kiseon KIM, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Robust Recursive Least Square Algorithm against Impulsive Noise},
year={2004},
volume={E87-A},
number={9},
pages={2463-2465},
abstract={In this paper, we propose a robust adaptive algorithm for impulsive noise suppression. The perturbation of the input signal as well as the perturbation of the estimation error are restricted by M-estimation. The threshold used in M-estimation is obtained from the proposed adaptive variance estimation. Simulations show that the proposed algorithm is less vulnerable to the impulsive noise than the conventional algorithm.},
keywords={},
doi={},
ISSN={},
month={September},}
Copy
TY - JOUR
TI - A Robust Recursive Least Square Algorithm against Impulsive Noise
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2463
EP - 2465
AU - Seong-Joon BAEK
AU - Jinyoung KIM
AU - Dae-Jin KIM
AU - Dong-Soo HAR
AU - Kiseon KIM
PY - 2004
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E87-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2004
AB - In this paper, we propose a robust adaptive algorithm for impulsive noise suppression. The perturbation of the input signal as well as the perturbation of the estimation error are restricted by M-estimation. The threshold used in M-estimation is obtained from the proposed adaptive variance estimation. Simulations show that the proposed algorithm is less vulnerable to the impulsive noise than the conventional algorithm.
ER -
English
