A Proportion-Sign Algorithm for Adaptive Filtering and Its Performance Analysis
Summary :
A new steepest descent linear adaptive algorithm, called the proportion-sign algorithm (PSA), is introduced and its performance analysis is presented when the signals are from zero-mean jointly stationary Gaussian processes. The PSA improves the convergence speed over the least mean square (LMS) algorithm without overly degrading the steady-state error performance and has the robustness to impulsive interference occurring in the desired response by adding a minimal amount of computational complexity. Computer simulations are presented that show these advantages of the PSA over the LMS algorithm and demonstrate a close match between theoretical and empirical results to verify our analysis.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E77-A No.9 pp.1502-1509
- Publication Date
- 1994/09/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Adaptive Signal Processing
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Seung Chan BANG, Souguil ANN, "A Proportion-Sign Algorithm for Adaptive Filtering and Its Performance Analysis" in IEICE TRANSACTIONS on Fundamentals,
vol. E77-A, no. 9, pp. 1502-1509, September 1994, doi: .
Abstract: A new steepest descent linear adaptive algorithm, called the proportion-sign algorithm (PSA), is introduced and its performance analysis is presented when the signals are from zero-mean jointly stationary Gaussian processes. The PSA improves the convergence speed over the least mean square (LMS) algorithm without overly degrading the steady-state error performance and has the robustness to impulsive interference occurring in the desired response by adding a minimal amount of computational complexity. Computer simulations are presented that show these advantages of the PSA over the LMS algorithm and demonstrate a close match between theoretical and empirical results to verify our analysis.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e77-a_9_1502/_p
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@ARTICLE{e77-a_9_1502,
author={Seung Chan BANG, Souguil ANN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Proportion-Sign Algorithm for Adaptive Filtering and Its Performance Analysis},
year={1994},
volume={E77-A},
number={9},
pages={1502-1509},
abstract={A new steepest descent linear adaptive algorithm, called the proportion-sign algorithm (PSA), is introduced and its performance analysis is presented when the signals are from zero-mean jointly stationary Gaussian processes. The PSA improves the convergence speed over the least mean square (LMS) algorithm without overly degrading the steady-state error performance and has the robustness to impulsive interference occurring in the desired response by adding a minimal amount of computational complexity. Computer simulations are presented that show these advantages of the PSA over the LMS algorithm and demonstrate a close match between theoretical and empirical results to verify our analysis.},
keywords={},
doi={},
ISSN={},
month={September},}
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TY - JOUR
TI - A Proportion-Sign Algorithm for Adaptive Filtering and Its Performance Analysis
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1502
EP - 1509
AU - Seung Chan BANG
AU - Souguil ANN
PY - 1994
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E77-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 1994
AB - A new steepest descent linear adaptive algorithm, called the proportion-sign algorithm (PSA), is introduced and its performance analysis is presented when the signals are from zero-mean jointly stationary Gaussian processes. The PSA improves the convergence speed over the least mean square (LMS) algorithm without overly degrading the steady-state error performance and has the robustness to impulsive interference occurring in the desired response by adding a minimal amount of computational complexity. Computer simulations are presented that show these advantages of the PSA over the LMS algorithm and demonstrate a close match between theoretical and empirical results to verify our analysis.
ER -
English
