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dc.contributor.authorBabadi, Behtash
dc.contributor.authorKalouptsidis, Nicholas
dc.contributor.authorTarokh, Vahid
dc.date.accessioned2011-01-26T14:16:15Z
dc.date.issued2010
dc.identifier.citationBabadi, Behtash, Nicholas Kalouptsidis, and Vahid Tarokh. 2010. SPARLS: The sparse RLS algorithm. IEEE Transactions on Signal Processing 58(8): 4013-4025.en_US
dc.identifier.issn1053-587Xen_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:4687196
dc.description.abstractWe develop a recursive ${cal L}_{1}$-regularized least squares (SPARLS) algorithm for the estimation of a sparse tap-weight vector in the adaptive filtering setting. The SPARLS algorithm exploits noisy observations of the tap-weight vector output stream and produces its estimate using an expectation-maximization type algorithm. We prove the convergence of the SPARLS algorithm to a near-optimal estimate in a stationary environment and present analytical results for the steady state error. Simulation studies in the context of channel estimation, employing multipath wireless channels, show that the SPARLS algorithm has significant improvement over the conventional widely used recursive least squares (RLS) algorithm in terms of mean squared error (MSE). Moreover, these simulation studies suggest that the SPARLS algorithm (with slight modifications) can operate with lower computational requirements than the RLS algorithm, when applied to tap-weight vectors with fixed support.en_US
dc.description.sponsorshipEngineering and Applied Sciencesen_US
dc.language.isoen_USen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.isversionofdoi:10.1109/TSP.2010.2048103en_US
dash.licenseOAP
dc.subjectadaptive filtersen_US
dc.subjectcompressed sensingen_US
dc.subjectsparse system identificationen_US
dc.titleSPARLS: The Sparse RLS Algorithmen_US
dc.typeJournal Articleen_US
dc.description.versionAccepted Manuscripten_US
dc.relation.journalIEEE Transactions on Signal Processingen_US
dash.depositing.authorTarokh, Vahid
dc.date.available2011-01-26T14:16:15Z
dc.identifier.doi10.1109/TSP.2010.2048103*
dash.contributor.affiliatedTarokh, Vahid
dash.contributor.affiliatedBabadi, Behtash


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