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Proximal Mappings Involving Almost Structured Matrices

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dc.contributor.authorBayram, Ilker
dc.date.accessioned2026-01-26T01:04:29Z
dc.date.issued2015-12-01
dc.description.abstractWe consider a minimization problem where the cost function consists of the sum of a quadratic data fidelity term and a penalty term. The quadratic involves a matrix $H$ that can be embedded into a larger matrix $\mathtilde{H}$ where multiplication with the inverse of $I + \alpha {\mathtilde{H}^T} \mathtilde{H}$ can be efficiently performed. We discuss how to take advantage of this property when the Douglas-Rachford algorithm is utilized.
dc.description.urihttps://doi.org/10.1109/lsp.2015.2476381
dc.description.urihttps://doi.org/10.1109/LSP.2015.2476381
dc.description.urihttps://dx.doi.org/10.1109/lsp.2015.2476381
dc.description.urihttps://aperta.ulakbim.gov.tr/record/81709
dc.identifier.doi10.1109/lsp.2015.2476381
dc.identifier.eissn1558-2361
dc.identifier.endpage2268
dc.identifier.issn1070-9908
dc.identifier.openairedoi_dedup___::b6363e572534dab204c066fc9f8a1801
dc.identifier.startpage2264
dc.identifier.urihttps://hdl.handle.net/11527/55378
dc.identifier.volume22
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartofIEEE Signal Processing Letters
dc.rightsOPEN
dc.sdg.typeGoal 2: Zero Hunger
dc.titleProximal Mappings Involving Almost Structured Matrices
dc.typeArticle
dspace.entity.typePublication

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