dc.creatorResende, LS
dc.creatorRomano, JMT
dc.creatorBellanger, MGB
dc.date2004
dc.dateMAR
dc.date2014-11-18T09:29:21Z
dc.date2015-11-26T16:53:35Z
dc.date2014-11-18T09:29:21Z
dc.date2015-11-26T16:53:35Z
dc.date.accessioned2018-03-28T23:40:42Z
dc.date.available2018-03-28T23:40:42Z
dc.identifierIeee Transactions On Signal Processing. Ieee-inst Electrical Electronics Engineers Inc, v. 52, n. 3, n. 636, n. 644, 2004.
dc.identifier1053-587X
dc.identifierWOS:000189128100007
dc.identifier10.1109/TSP.2003.822351
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/74408
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/74408
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/74408
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1276623
dc.descriptionThis paper proposes a new structure for split transversal filtering and introduces the optimum split Wiener filter. The approach consists of combining the idea of split filtering with a linearly constrained optimization scheme. Furthermore, a continued split procedure, which leads to a multisplit filter structure, is considered. It is shown that the multisplit transform is not an input whitening transformation. Instead, it increases the diagonalization factor of the input signal correlation matrix without affecting its eigenvalue spread. A power normalized, time-varying step-size least mean square (LMS) algorithm, which exploits the nature of the transformed input correlation matrix, is proposed for updating the adaptive filter coefficients. The multisplit approach is extended to linear-phase adaptive filtering and linear prediction. The optimum symmetric and antisymmetric linear-phase Wiener filters are presented. Simulation results enable. us to evaluate the performance of the multisplit LMS algorithm.
dc.description52
dc.description3
dc.description636
dc.description644
dc.languageen
dc.publisherIeee-inst Electrical Electronics Engineers Inc
dc.publisherPiscataway
dc.publisherEUA
dc.relationIeee Transactions On Signal Processing
dc.relationIEEE Trans. Signal Process.
dc.rightsfechado
dc.rightshttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dc.sourceWeb of Science
dc.subjectadaptive filtering
dc.subjectlinear-phase filtering
dc.subjectlinear prediction
dc.subjectlinearly constrained filtering
dc.subjectsplit filtering
dc.subjectWiener filtering
dc.titleSplit Wiener filtering with application in adaptive systems
dc.typeArtículos de revistas


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