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dc.contributor.authorFletcher, A.K.en_US
dc.contributor.authorRangan, S.en_US
dc.contributor.authorGoyal, V.K.en_US
dc.date.accessioned2021-05-12T16:00:50Z
dc.date.available2021-05-12T16:00:50Z
dc.date.issued2012-11
dc.identifier.citationA.K. Fletcher, S. Rangan, V.K. Goyal. 2012. "Ranked Sparse Signal Support Detection." IEEE Transactions on Signal Processing, Volume 60, Issue 11, pp. 5919 - 5931. https://doi.org/10.1109/tsp.2012.2208957
dc.identifier.issn1053-587X
dc.identifier.issn1941-0476
dc.identifier.urihttps://hdl.handle.net/2144/42543
dc.description.abstractThis paper considers the problem of detecting the support (sparsity pattern) of a sparse vector from random noisy measurements. Conditional power of a component of the sparse vector is defined as the energy conditioned on the component being nonzero. Analysis of a simplified version of orthogonal matching pursuit (OMP) called sequential OMP (SequOMP) demonstrates the importance of knowledge of the rankings of conditional powers. When the simple SequOMP algorithm is applied to components in nonincreasing order of conditional power, the detrimental effect of dynamic range on thresholding performance is eliminated. Furthermore, under the most favorable conditional powers, the performance of SequOMP approaches maximum likelihood performance at high signal-to-noise ratio.en_US
dc.format.extentp. 5919 - 5931en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.ispartofIEEE Transactions on Signal Processing
dc.subjectCompressed sensingen_US
dc.subjectConvex optimizationen_US
dc.subjectLassoen_US
dc.subjectMaximum likelihood estimationen_US
dc.subjectOrthogonal matching pursuiten_US
dc.subjectRandom matricesen_US
dc.subjectSparse Bayesian learningen_US
dc.subjectSparsityen_US
dc.subjectThresholdingen_US
dc.subjectNetworking & telecommunicationsen_US
dc.titleRanked sparse signal support detectionen_US
dc.typeArticleen_US
dc.description.versionFirst author draften_US
dc.identifier.doi10.1109/tsp.2012.2208957
pubs.elements-sourcecrossrefen_US
pubs.notesEmbargo: No embargoen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, College of Engineeringen_US
pubs.organisational-groupBoston University, College of Engineering, Department of Electrical & Computer Engineeringen_US
pubs.publication-statusPublisheden_US
dc.identifier.orcid0000-0001-8471-7049 (Goyal, VK)
dc.identifier.mycv36883


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