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However, these iterative methods may require a large number of iterations and this reduces their usefulness. This paper develops a computationally attractive linearized Bregman algorithm by projecting the problem to be solved into an appropriately chosen low-dimensional Krylov subspace. The projection reduces the computational effort required for each iteration. A variant of this solution method, in which nonnegativity of each computed iterate is imposed, also is described. Extensive numerical examples illustrate the performance of the proposed methods.<\/jats:p>","DOI":"10.1007\/s11075-020-01004-6","type":"journal-article","created":{"date-parts":[[2020,9,7]],"date-time":"2020-09-07T17:02:55Z","timestamp":1599498175000},"page":"1177-1200","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Linearized Krylov subspace Bregman iteration with nonnegativity constraint"],"prefix":"10.1007","volume":"87","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6456-4150","authenticated-orcid":false,"given":"Alessandro","family":"Buccini","sequence":"first","affiliation":[]},{"given":"Mirjeta","family":"Pasha","sequence":"additional","affiliation":[]},{"given":"Lothar","family":"Reichel","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,9,7]]},"reference":[{"key":"1004_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cam.2016.12.023","volume":"319","author":"Z-Z Bai","year":"2017","unstructured":"Bai, Z.-Z., Buccini, A., Hayami, K., Reichel, L., Yin, J.-F., Zheng, N.: Modulus-based iterative methods for constrained Tikhonov regularization. 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