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High Resolution Spectral Estimation using BP via Compressive Sensing

dc.contributor.authorDuarte, Isabel
dc.contributor.authorVieira, José M. N.
dc.contributor.authorFerreira, Paulo J S G
dc.contributor.authorAlbuquerque, Daniel
dc.date.accessioned2015-01-09T10:09:55Z
dc.date.available2015-01-09T10:09:55Z
dc.date.issued2012-10
dc.description.abstractIn this paper we propose a method based on compressed sensing (CS) for estimating the spectrum of a signal written as a linear combination of a small number of sinusoids. In the case of finite-length signals, the Fourier coefficients are not exactly sparse due to the leakage effect if the frequency is not a multiple of the fundamental frequency; To overcome this problem our algorithm transform the DFT basis into a frame with a larger number of vectors, by inserting columns between some of the initial ones. The algorithm applies Basis Pursuit (BP) to estimate the sinusoids amplitude, phase and frequency.por
dc.identifier.isbn978-988-19251-6-9
dc.identifier.urihttp://hdl.handle.net/10400.19/2506
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherS. I. Ao and Craig Douglas and W. S. Grundfest and Jon Burgstonepor
dc.subjectBasis Pursuitpor
dc.subjectcompressive sensingpor
dc.subjectspectral estimationpor
dc.subjectsparse representationspor
dc.titleHigh Resolution Spectral Estimation using BP via Compressive Sensingpor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceSan Francisco, USApor
oaire.citation.endPage704por
oaire.citation.startPage699por
oaire.citation.titleProceedings of the World Congress on Engineering and Computer Science 2012por
oaire.citation.volumeIpor
rcaap.rightsclosedAccesspor
rcaap.typearticlepor

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