Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/6085
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Applied Mathematics | - |
dc.creator | Yu, G | - |
dc.creator | Niu, S | - |
dc.creator | Ma, J | - |
dc.creator | Song, Y | - |
dc.date.accessioned | 2014-12-11T08:24:44Z | - |
dc.date.available | 2014-12-11T08:24:44Z | - |
dc.identifier.issn | 1085-3375 (print) | - |
dc.identifier.issn | 1687-0409 (online) | - |
dc.identifier.uri | http://hdl.handle.net/10397/6085 | - |
dc.language.iso | en | en_US |
dc.publisher | Hindawi Publishing Corporation | en_US |
dc.rights | Copyright © 2013 Gaohang Yu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | en_US |
dc.title | An adaptive prediction-correction method for solving large-scale nonlinear systems of monotone equations with applications | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 1 | - |
dc.identifier.epage | 13 | - |
dc.identifier.volume | 2013 | - |
dc.identifier.doi | 10.1155/2013/619123 | - |
dcterms.abstract | Combining multivariate spectral gradient method with projection scheme, this paper presents an adaptive prediction-correction method for solving large-scale nonlinear systems of monotone equations. The proposed method possesses some favorable properties: (1) it is progressive step by step, that is, the distance between iterates and the solution set is decreasing monotonically; (2) global convergence result is independent of the merit function and its Lipschitz continuity; (3) it is a derivative-free method and could be applied for solving large-scale nonsmooth equations due to its lower storage requirement. Preliminary numerical results show that the proposed method is very effective. Some practical applications of the proposed method are demonstrated and tested on sparse signal reconstruction, compressed sensing, and image deconvolution problems. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Abstract and applied analysis, v. 2013, 619123, p.1-13 | - |
dcterms.isPartOf | Abstract and applied analysis | - |
dcterms.issued | 2013 | - |
dc.identifier.isi | WOS:000319192400001 | - |
dc.identifier.scopus | 2-s2.0-84878740671 | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Yu_an_adaptive_predication.pdf | 1.82 MB | Adobe PDF | View/Open |
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