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dc.contributor.authorArdekani, Iman
dc.contributor.authorAbdulla, W. H.
dc.date.accessioned2015-03-10T19:46:20Z
dc.date.available2015-03-10T19:46:20Z
dc.date.issued2013
dc.identifier.issn1751-9675
dc.identifier.urihttps://hdl.handle.net/10652/2596
dc.description.abstractThis study represents a stochastic model for the adaptation process performed on adaptive control systems by the filtered-x least-mean-square (FxLMS) algorithm. The main distinction of this model is that it is derived without using conventional simplifying assumptions regarding the physical plant to be controlled. This model is then used to derive a set of closed-form mathematical expressions for formulating steady-state performance, stability condition and learning rate of the FxLMS adaptation process. These expressions are the most general expressions, which have been proposed so far. It is shown that some previously derived expressions can be obtained from the proposed expressions as special and simplified cases. In addition to computer simulations, different experiments with a real-time control setup confirm the validity of the theoretical findings.en_NZ
dc.language.isoenen_NZ
dc.publisherThe Institution of Engineering and Technologyen_NZ
dc.relation.urihttp://ieeexplore.ieee.org/Xplore/defdeny.jsp?url=http%3A%2F%2Fieeexplore.ieee.org%2Fstamp%2Fstamp.jsp%3Ftp%3D%26arnumber%3D6564492%26userType%3Dinst&denyReason=-134&arnumber=6564492&productsMatched=null&userType=insten_NZ
dc.subjectstochastic modellingen_NZ
dc.subjectFxLMSen_NZ
dc.subjectcontrol systemsen_NZ
dc.subjectadaptive controlen_NZ
dc.subjectcontrollersen_NZ
dc.titleOn the stochastic modeling and analysis of FxLMS adaptation algorithmen_NZ
dc.title.alternativeStochastic modelling and analysis of filtered-xleast-mean-square adaptation algorithmen_NZ
dc.typeJournal Articleen_NZ
dc.rights.holderThe Institution of Engineering and Technologyen_NZ
dc.identifier.doidoi: 10.1049/iet-spr.2012.0090en_NZ
dc.subject.marsden080101 Adaptive Agents and Intelligent Roboticsen_NZ
dc.identifier.bibliographicCitationArdekani, I.T., and Abdulla, W.H. (2013). On the stochastic modeling and analysis of FxLMS adaptation algorithm. IET Signal Processing. 7(6) : (pp. 486-496)en_NZ
unitec.institutionUnitec Institute of Technologyen_NZ
unitec.publication.spage486en_NZ
unitec.publication.lpage496en_NZ
unitec.publication.volume7(6)en_NZ
unitec.publication.titleIET Signal Processingen_NZ
unitec.peerreviewedyesen_NZ
dc.contributor.affiliationUniversity of Aucklanden_NZ
unitec.identifier.roms55170en_NZ
unitec.institution.studyareaComputing


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