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dc.contributor.authorWang, Y.
dc.contributor.authorZhou, Guanglu
dc.contributor.authorCaccetta, Louis
dc.contributor.authorLiu, Wan-Quan
dc.date.accessioned2017-03-15T22:02:16Z
dc.date.available2017-03-15T22:02:16Z
dc.date.created2017-02-24T00:09:32Z
dc.date.issued2011
dc.identifier.citationWang, Y. and Zhou, G. and Caccetta, L. and Liu, W. 2011. An Alternative Lagrange-Dual based Algorithm for Sparse Signal Reconstruction. IEEE Transactions on Signal Processing. 59 (4): pp. 1895-1901.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/49079
dc.identifier.doi10.1109/TSP.2010.2103066
dc.description.abstract

In this correspondence, we propose a new Lagrange-dual reformulation associated with an l1 -norm minimization problem for sparse signal reconstruction. There are two main advantages of our proposed approach. First, the number of the variables in the reformulated optimization problem is much smaller than that in the original problem when the dimension of measurement vector is much less than the size of the original signals; Second, the new problem is smooth and convex, and hence it can be solved by many state of the art gradient-type algorithms efficiently. The efficiency and performance of the proposed algorithm are validated via theoretical analysis as well as some illustrative numerical examples.

dc.publisherI E E E
dc.titleAn Alternative Lagrange-Dual based Algorithm for Sparse Signal Reconstruction
dc.typeJournal Article
dcterms.source.volume59
dcterms.source.startPage1895
dcterms.source.endPage1901
dcterms.source.issn1053-587X
dcterms.source.titleIEEE Transactions on Signal Processing
curtin.departmentDepartment of Mathematics and Statistics
curtin.accessStatusFulltext not available


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