Please use this identifier to cite or link to this item: https://doi.org/10.1109/JSTSP.2011.2160711
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dc.titleGini index as sparsity measure for signal reconstruction from compressive samples
dc.contributor.authorZonoobi, D.
dc.contributor.authorKassim, A.A.
dc.contributor.authorVenkatesh, Y.V.
dc.date.accessioned2014-10-07T04:29:11Z
dc.date.available2014-10-07T04:29:11Z
dc.date.issued2011-09
dc.identifier.citationZonoobi, D., Kassim, A.A., Venkatesh, Y.V. (2011-09). Gini index as sparsity measure for signal reconstruction from compressive samples. IEEE Journal on Selected Topics in Signal Processing 5 (5) : 927-932. ScholarBank@NUS Repository. https://doi.org/10.1109/JSTSP.2011.2160711
dc.identifier.issn19324553
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/82420
dc.description.abstractSparsity is a fundamental concept in compressive sampling of signals/images, which is commonly measured using the 0 norm, even though, in practice, the 1 or the p (0< p< 1) (pseudo-) norm is preferred. In this paper, we explore the use of the Gini index (GI), of a discrete signal, as a more effective measure of its sparsity for a significantly improved performance in its reconstruction from compressive samples. We also successfully incorporate the GI into a stochastic optimization algorithm for signal reconstruction from compressive samples and illustrate our approach with both synthetic and real signals/images. © 2011 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/JSTSP.2011.2160711
dc.sourceScopus
dc.subjectCompressive sensing (CS)
dc.subjectGini index (GI)
dc.subjectnon-convex optimization
dc.subjectsimultaneous perturbation stochastic approximation (SPSA)
dc.subjectsparsity measures
dc.typeArticle
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.contributor.departmentINTERACTIVE & DIGITAL MEDIA INSTITUTE
dc.description.doi10.1109/JSTSP.2011.2160711
dc.description.sourcetitleIEEE Journal on Selected Topics in Signal Processing
dc.description.volume5
dc.description.issue5
dc.description.page927-932
dc.identifier.isiut000294012200004
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