ZA-APA with Adaptive Zero Attractor Controller for Variable Sparsity Environment

The zero attraction affine projection algorithm (ZA-APA) achieves better performance in terms of convergence rate and steady state error than standard APA when the system is sparse. It uses l1 norm penalty to exploit sparsity of the channel. The performance of ZA-APA depends on the value of zero att...

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Main Authors: S. Radhika, A. Chandrasekar, S. Nirmalraj
Format: Article
Language:English
Published: Polish Academy of Sciences 2020-12-01
Series:International Journal of Electronics and Telecommunications
Subjects:
Online Access:https://journals.pan.pl/Content/117124/PDF/93_2210_RADHIKA_new.pdf
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author S. Radhika
A. Chandrasekar
S. Nirmalraj
author_facet S. Radhika
A. Chandrasekar
S. Nirmalraj
author_sort S. Radhika
collection DOAJ
description The zero attraction affine projection algorithm (ZA-APA) achieves better performance in terms of convergence rate and steady state error than standard APA when the system is sparse. It uses l1 norm penalty to exploit sparsity of the channel. The performance of ZA-APA depends on the value of zero attractor controller. Moreover a fixed attractor controller is not suitable for varying sparsity environment. This paper proposes an optimal adaptive zero attractor controller based on Mean Square Deviation (MSD) error to work in variable sparsity environment. Experiments were conducted to prove the suitability of the proposed algorithm for identification of unknown variable sparse system.
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spelling doaj.art-e52283e533ca47edb33945e9adeca8652022-12-22T02:33:09ZengPolish Academy of SciencesInternational Journal of Electronics and Telecommunications2081-84912300-19332020-12-01vol. 66No 4695700https://doi.org/10.24425/ijet.2020.134029ZA-APA with Adaptive Zero Attractor Controller for Variable Sparsity EnvironmentS. RadhikaA. ChandrasekarS. NirmalrajThe zero attraction affine projection algorithm (ZA-APA) achieves better performance in terms of convergence rate and steady state error than standard APA when the system is sparse. It uses l1 norm penalty to exploit sparsity of the channel. The performance of ZA-APA depends on the value of zero attractor controller. Moreover a fixed attractor controller is not suitable for varying sparsity environment. This paper proposes an optimal adaptive zero attractor controller based on Mean Square Deviation (MSD) error to work in variable sparsity environment. Experiments were conducted to prove the suitability of the proposed algorithm for identification of unknown variable sparse system.https://journals.pan.pl/Content/117124/PDF/93_2210_RADHIKA_new.pdfzero attraction apasparse channelconvergencesteady state mean square errorvariable zero attraction controller
spellingShingle S. Radhika
A. Chandrasekar
S. Nirmalraj
ZA-APA with Adaptive Zero Attractor Controller for Variable Sparsity Environment
International Journal of Electronics and Telecommunications
zero attraction apa
sparse channel
convergence
steady state mean square error
variable zero attraction controller
title ZA-APA with Adaptive Zero Attractor Controller for Variable Sparsity Environment
title_full ZA-APA with Adaptive Zero Attractor Controller for Variable Sparsity Environment
title_fullStr ZA-APA with Adaptive Zero Attractor Controller for Variable Sparsity Environment
title_full_unstemmed ZA-APA with Adaptive Zero Attractor Controller for Variable Sparsity Environment
title_short ZA-APA with Adaptive Zero Attractor Controller for Variable Sparsity Environment
title_sort za apa with adaptive zero attractor controller for variable sparsity environment
topic zero attraction apa
sparse channel
convergence
steady state mean square error
variable zero attraction controller
url https://journals.pan.pl/Content/117124/PDF/93_2210_RADHIKA_new.pdf
work_keys_str_mv AT sradhika zaapawithadaptivezeroattractorcontrollerforvariablesparsityenvironment
AT achandrasekar zaapawithadaptivezeroattractorcontrollerforvariablesparsityenvironment
AT snirmalraj zaapawithadaptivezeroattractorcontrollerforvariablesparsityenvironment