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Generalized Sampling and Infinite-Dimensional Compressed Sensing

cam.issuedOnline2015-08-20
dc.contributor.authorAdcock, B
dc.contributor.authorHansen, AC
dc.date.accessioned2018-10-18T10:20:39Z
dc.date.available2018-10-18T10:20:39Z
dc.date.issued2016
dc.description.abstract© 2015, SFoCM. We introduce and analyze a framework and corresponding method for compressed sensing in infinite dimensions. This extends the existing theory from finite-dimensional vector spaces to the case of separable Hilbert spaces. We explain why such a new theory is necessary by demonstrating that existing finite-dimensional techniques are ill suited for solving a number of key problems. This work stems from recent developments in generalized sampling theorems for classical (Nyquist rate) sampling that allows for reconstructions in arbitrary bases. A conclusion of this paper is that one can extend these ideas to allow for significant subsampling of sparse or compressible signals. Central to this work is the introduction of two novel concepts in sampling theory, the stable sampling rate and the balancing property, which specify how to appropriately discretize an infinite-dimensional problem.
dc.identifier.doi10.17863/CAM.31472
dc.identifier.eissn1615-3383
dc.identifier.issn1615-3375
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/284101
dc.language.isoeng
dc.publisherSpringer Science and Business Media LLC
dc.publisher.urlhttp://dx.doi.org/10.1007/s10208-015-9276-6
dc.subjectCompressed sensing
dc.subjectHilbert spaces
dc.subjectGeneralized sampling
dc.subjectUneven sections
dc.titleGeneralized Sampling and Infinite-Dimensional Compressed Sensing
dc.typeArticle
dcterms.dateAccepted2015-08-01
prism.endingPage1323
prism.issueIdentifier5
prism.publicationDate2016
prism.publicationNameFoundations of Computational Mathematics
prism.startingPage1263
prism.volume16
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/L003457/1)
rioxxterms.licenseref.startdate2016-10-01
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.typeJournal Article/Review
rioxxterms.versionAM
rioxxterms.versionofrecord10.1007/s10208-015-9276-6

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