Please use this identifier to cite or link to this item: https://doi.org/10.1090/S0025-5718-09-02242-X
DC FieldValue
dc.titleConvergence of the linearized Bregman iteration for ℓ1-norm minimization
dc.contributor.authorCai, J.-F.
dc.contributor.authorOsher, S.
dc.contributor.authorShen, Z.
dc.date.accessioned2014-12-12T07:30:51Z
dc.date.available2014-12-12T07:30:51Z
dc.date.issued2009-10
dc.identifier.citationCai, J.-F., Osher, S., Shen, Z. (2009-10). Convergence of the linearized Bregman iteration for ℓ1-norm minimization. Mathematics of Computation 78 (268) : 2127-2136. ScholarBank@NUS Repository. https://doi.org/10.1090/S0025-5718-09-02242-X
dc.identifier.issn00255718
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/115657
dc.description.abstractOne of the key steps in compressed sensing is to solve the basis pursuit problem min urnu1: Au=f. Bregman iteration was very successfully used to solve this problem in [40]. Also, a simple and fast iterative algorithm based on linearized Bregman iteration was proposed in [40], which is described in detail with numerical simulations in [35]. A convergence analysis of the smoothed version of this algorithm was given in [11]. The purpose of this paper is to prove that the linearized Bregman iteration proposed in [40] for the basis pursuit problem indeed converges. © 2009 American Mathematical Society.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1090/S0025-5718-09-02242-X
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentTEMASEK LABORATORIES
dc.contributor.departmentMATHEMATICS
dc.description.doi10.1090/S0025-5718-09-02242-X
dc.description.sourcetitleMathematics of Computation
dc.description.volume78
dc.description.issue268
dc.description.page2127-2136
dc.identifier.isiut000270766200012
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