Novel Sparse Algorithms based on Lyapunov Stability for Adaptive System Identification

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dc.contributor.authorPogula, Rakesh
dc.contributor.authorKumar, T. Kishore
dc.contributor.authorAlbu, Felix
dc.coverage.issue1cs
dc.coverage.volume27cs
dc.date.accessioned2018-06-18T10:30:19Z
dc.date.available2018-06-18T10:30:19Z
dc.date.issued2018-04cs
dc.description.abstractAdaptive filters are extensively used in the identification of an unknown system. Unlike several gradient-search based adaptive filtering techniques, the Lyapunov Theory-based Adaptive Filter offers improved convergence and stability. When the system is described by a sparse model, the performance of Lyapunov Adaptive (LA) filter is degraded since it fails to exploit the system sparsity. In this paper, the Zero-Attracting Lyapunov Adaptation algorithm (ZA-LA), the Reweighted Zero-Attracting Lyapunov Adaptation algorithm (RZA-LA) and an affine combination scheme of the LA and proposed ZA-LA filters are proposed. The ZA-LA algorithm is based on ℓ1-norm relaxation while the RZA-LA algorithm uses a log-sum penalty to accelerate convergence when identifying sparse systems. It is shown by simulations that the proposed algorithms can achieve better convergence than the existing LMS/LA filter for a sparse system, while the affine combination scheme is robust in identifying systems with variable sparsity.en
dc.formattextcs
dc.format.extent270-280cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRadioengineering. 2018 vol. 27, č. 1, s. 270-280. ISSN 1210-2512cs
dc.identifier.doi10.13164/re.2018.0270en
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/82984
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttps://www.radioeng.cz/fulltexts/2018/18_01_0270_0280.pdfcs
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectSparse system identificationen
dc.subjectLyapunov adaptive filter (LA)en
dc.subjectℓ1-normen
dc.subjectZero-attracting LAen
dc.subjectReweighted ZA-LAen
dc.subjectAffine combinationen
dc.subjectConvergenceen
dc.subjectMean square deviationen
dc.subjectMean square erroren
dc.titleNovel Sparse Algorithms based on Lyapunov Stability for Adaptive System Identificationen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
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