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dc.contributor.authorRomer, F.en_US
dc.contributor.authorLavrenko, A.en_US
dc.contributor.authorDel Galdo, G.en_US
dc.contributor.authorHotz, T.en_US
dc.contributor.authorArıkan, Orhanen_US
dc.contributor.authorThoma, R. S.en_US
dc.coverage.spatialPacific Grove, CA, USA
dc.date.accessioned2016-02-08T12:15:27Z
dc.date.available2016-02-08T12:15:27Z
dc.date.issued2015-11en_US
dc.identifier.issn1058-6393
dc.identifier.urihttp://hdl.handle.net/11693/28252
dc.descriptionDate of Conference: 2-5 Nov. 2014
dc.descriptionConference name: 48th Asilomar Conference on Signals, Systems and Computers, 2014
dc.description.abstractIn this paper we discuss the estimation of the spar-sity order for a Compressed Sensing scenario where only a single snapshot is available. We demonstrate that a specific design of the sensing matrix based on Khatri-Rao products enables us to transform this problem into the estimation of a matrix rank in the presence of additive noise. Thereby, we can apply existing model order selection algorithms to determine the sparsity order. The matrix is a rearranged version of the observation vector which can be constructed by concatenating a series of non-overlapping or overlapping blocks of the original observation vector. In both cases, a Khatri-Rao structured measurement matrix is required with the main difference that in the latter case, one of the factors must be a Vandermonde matrix. We discuss the choice of the parameters and show that an increasing amount of block overlap improves the sparsity order estimation but it increases the coherence of the sensing matrix. We also explain briefly that the proposed measurement matrix design introduces certain multilinear structures into the observations which enables us to apply tensor-based signal processing, e.g., for enhanced denoising or improved sparsity order estimation. © 2014 IEEE.en_US
dc.language.isoEnglishen_US
dc.source.titleConference Record - Asilomar Conference on Signals, Systems and Computersen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/ACSSC.2014.7094653en_US
dc.subjectAdditive noiseen_US
dc.subjectProduct designen_US
dc.subjectSignal processingen_US
dc.subjectSignal reconstructionen_US
dc.subjectKhatri-Rao productsen_US
dc.subjectMatrix ranken_US
dc.subjectMeasurement matrixen_US
dc.subjectModel-order selectionen_US
dc.subjectObservation vectorsen_US
dc.subjectOrder estimationen_US
dc.subjectSingle snapshotsen_US
dc.subjectVandermonde matrixen_US
dc.subjectCompressed sensingen_US
dc.titleSparsity order estimation for single snapshot compressed sensingen_US
dc.typeConference Paperen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.spage1220en_US
dc.citation.epage1224en_US
dc.identifier.doi10.1109/ACSSC.2014.7094653en_US
dc.publisherIEEEen_US
dc.contributor.bilkentauthorArıkan, Orhan
buir.contributor.orcidArıkan, Orhan|0000-0002-3698-8888en_US


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