IEICE TRANSACTIONS on Fundamentals
Noise Constrained Data-Reusing Adaptive Algorithms for System Identification
Summary :
We present a new framework of the data-reusing (DR) adaptive algorithms by incorporating a constraint on noise, referred to as a noise constraint. The motivation behind this work is that the use of the statistical knowledge of the channel noise can contribute toward improving the convergence performance of an adaptive filter in identifying a noisy linear finite impulse response (FIR) channel. By incorporating the noise constraint into the cost function of the DR adaptive algorithms, the noise constrained DR (NC-DR) adaptive algorithms are derived. Experimental results clearly indicate their superior performance over the conventional DR ones.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E95-A No.6 pp.1084-1087
- Publication Date
- 2012/06/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E95.A.1084
- Type of Manuscript
- LETTER
- Category
- Digital Signal Processing
Authors
Keyword
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Young-Seok CHOI, Woo-Jin SONG, "Noise Constrained Data-Reusing Adaptive Algorithms for System Identification" in IEICE TRANSACTIONS on Fundamentals,
vol. E95-A, no. 6, pp. 1084-1087, June 2012, doi: 10.1587/transfun.E95.A.1084.
Abstract: We present a new framework of the data-reusing (DR) adaptive algorithms by incorporating a constraint on noise, referred to as a noise constraint. The motivation behind this work is that the use of the statistical knowledge of the channel noise can contribute toward improving the convergence performance of an adaptive filter in identifying a noisy linear finite impulse response (FIR) channel. By incorporating the noise constraint into the cost function of the DR adaptive algorithms, the noise constrained DR (NC-DR) adaptive algorithms are derived. Experimental results clearly indicate their superior performance over the conventional DR ones.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E95.A.1084/_p
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@ARTICLE{e95-a_6_1084,
author={Young-Seok CHOI, Woo-Jin SONG, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Noise Constrained Data-Reusing Adaptive Algorithms for System Identification},
year={2012},
volume={E95-A},
number={6},
pages={1084-1087},
abstract={We present a new framework of the data-reusing (DR) adaptive algorithms by incorporating a constraint on noise, referred to as a noise constraint. The motivation behind this work is that the use of the statistical knowledge of the channel noise can contribute toward improving the convergence performance of an adaptive filter in identifying a noisy linear finite impulse response (FIR) channel. By incorporating the noise constraint into the cost function of the DR adaptive algorithms, the noise constrained DR (NC-DR) adaptive algorithms are derived. Experimental results clearly indicate their superior performance over the conventional DR ones.},
keywords={},
doi={10.1587/transfun.E95.A.1084},
ISSN={1745-1337},
month={June},}
Copy
TY - JOUR
TI - Noise Constrained Data-Reusing Adaptive Algorithms for System Identification
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1084
EP - 1087
AU - Young-Seok CHOI
AU - Woo-Jin SONG
PY - 2012
DO - 10.1587/transfun.E95.A.1084
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E95-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 2012
AB - We present a new framework of the data-reusing (DR) adaptive algorithms by incorporating a constraint on noise, referred to as a noise constraint. The motivation behind this work is that the use of the statistical knowledge of the channel noise can contribute toward improving the convergence performance of an adaptive filter in identifying a noisy linear finite impulse response (FIR) channel. By incorporating the noise constraint into the cost function of the DR adaptive algorithms, the noise constrained DR (NC-DR) adaptive algorithms are derived. Experimental results clearly indicate their superior performance over the conventional DR ones.
ER -
English
