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Recovery analysis for weighted mixed ℓ2/ℓp minimization with 0 < p ≤ 1
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik. (Mathematical Statistics)ORCID-id: 0000-0001-5673-620X
2019 (engelsk)Inngår i: Journal of Computational and Applied Mathematics, ISSN 0377-0427, E-ISSN 1879-1778, Vol. 352, s. 12s. 210-222Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

We study the recovery conditions of weighted mixed ℓ2/ℓp (0 < p ≤ 1) minimization for block sparse signal reconstruction from compressed measurements when partial block support information is available. We show that the block p-restricted isometry property (RIP) can ensure the robust recovery. Moreover, we present the sufficient and necessary condition for the recovery by using weighted block p-null space property. The relationship between the block p-RIP and the weighted block p-null space property has been established. Finally, we illustrate our results with a series of numerical experiments.

sted, utgiver, år, opplag, sider
Elsevier, 2019. Vol. 352, s. 12s. 210-222
Emneord [en]
Compressive sensing, Prior support information, Block sparse, Non-convex minimization
HSV kategori
Forskningsprogram
matematisk statistik
Identifikatorer
URN: urn:nbn:se:umu:diva-141543DOI: 10.1016/j.cam.2018.11.031ISI: 000458713000015Scopus ID: 2-s2.0-85058940234OAI: oai:DiVA.org:umu-141543DiVA, id: diva2:1155309
Prosjekter
Statistical modelling and intelligent data sampling in MRI and PET measurements for cancer therapy assessment
Forskningsfinansiär
Swedish Research Council, 340-2013-5342
Merknad

Originally included in thesis in manuscript form.

Tilgjengelig fra: 2017-11-07 Laget: 2017-11-07 Sist oppdatert: 2023-03-24bibliografisk kontrollert

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Zhou, ZhiyongYu, Jun

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