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@article{
 title = {R(3)GMRES: INCLUDING PRIOR INFORMATION IN GMRES-TYPE METHODS FOR DISCRETE INVERSE PROBLEMS},
 type = {article},
 year = {2014},
 identifiers = {[object Object]},
 keywords = {ILL-POSED PROBLEMS,REGULARIZATION,inverse problems,large-scale problems,prior information,regularizing iterations},
 pages = {136-146},
 volume = {42},
 websites = {http://apps.webofknowledge.com.globalproxy.cvt.dk/full_record.do?product=UA&search_mode=GeneralSearch&qid=15&SID=R1gI9xzWGe5XCgFDbbu&page=1&doc=1},
 publisher = {KENT STATE UNIVERSITY, ETNA, DEPT MATHEMATICS & COMPUTER SCIENCE, KENT, OH 44242-0001 USA},
 id = {017f2049-5be6-30d1-818a-f5dad4e0e5c5},
 created = {2015-11-15T22:16:02.000Z},
 accessed = {2015-11-15},
 file_attached = {false},
 profile_id = {72235656-d597-370e-a1e5-8453c60fa280},
 group_id = {d0e361cc-e4f9-3361-a178-f7e6d1f6363f},
 last_modified = {2018-04-09T10:03:06.510Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Dong2014},
 private_publication = {false},
 abstract = {Lothar Reichel and his collaborators proposed several iterative algorithms that augment the underlying Krylov subspace with an additional low-dimensional subspace in order to produce improved regularized solutions. We take a closer look at this approach and investigate a particular Regularized Range-Restricted GMRES method, R(3)GMRES, with a subspace that represents prior information about the solution. We discuss the implementation of this approach and demonstrate its advantage by means of several test problems.},
 bibtype = {article},
 author = {Dong, Yiqiu and Garde, Henrik and Hansen, Per Christian},
 journal = {ELECTRONIC TRANSACTIONS ON NUMERICAL ANALYSIS}
}