An Array Recursive Least-Squares Algorithm With Generic Nonfading Regularization Matrix

dc.creatorTsakiris, Manolis
dc.creatorLopes, Cassio Guimarães
dc.creatorNascimento, Vitor Heloiz
dc.date.accessioned2012-10-19T01:46:08Z
dc.date.accessioned2018-07-04T14:51:28Z
dc.date.available2012-10-19T01:46:08Z
dc.date.available2018-07-04T14:51:28Z
dc.date.created2012-10-19T01:46:08Z
dc.date.issued2010
dc.identifierIEEE SIGNAL PROCESSING LETTERS, v.17, n.12, p.1001-1004, 2010
dc.identifier1070-9908
dc.identifierhttp://producao.usp.br/handle/BDPI/18611
dc.identifier10.1109/LSP.2010.2083652
dc.identifierhttp://dx.doi.org/10.1109/LSP.2010.2083652
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1615403
dc.description.abstractWe present a novel array RLS algorithm with forgetting factor that circumvents the problem of fading regularization, inherent to the standard exponentially-weighted RLS, by allowing for time-varying regularization matrices with generic structure. Simulations in finite precision show the algorithm`s superiority as compared to alternative algorithms in the context of adaptive beamforming.
dc.languageeng
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relationIeee Signal Processing Letters
dc.rightsCopyright IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.rightsrestrictedAccess
dc.subjectArrays
dc.subjectEquations
dc.subjectArray signal processing
dc.subjectComplexity theory
dc.subjectRobustness
dc.subjectEigenvalues and eigenfunctions
dc.subjectRLS
dc.subjectArray forms
dc.subjectregularization
dc.titleAn Array Recursive Least-Squares Algorithm With Generic Nonfading Regularization Matrix
dc.typeArtículos de revistas


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