1. You are Here：

Full metadata record
DC FieldValueLanguage
dc.contributor.authorLin, Pu-Hsuanen_US
dc.contributor.authorTsai, Shang-Hoen_US
dc.contributor.authorChuang, Gene C. -H.en_US
dc.date.accessioned2014-12-08T15:34:22Z-
dc.date.available2014-12-08T15:34:22Z-
dc.date.issued2013en_US
dc.identifier.isbn978-1-4799-0356-6en_US
dc.identifier.issn1520-6149en_US
dc.identifier.urihttp://hdl.handle.net/11536/23534-
dc.description.abstractThis paper proposes an orthogonal matching pursuit (OMP-) based recovering algorithm for compressive sensing problems. This algorithm can significantly improve recovering performance while it can still maintain reasonable computational complexity. Complexity analysis and simulation results are provided for the proposed algorithm and compared with other popular recovering schemes. We observe that the proposed algorithm can significantly improve the exact recovering performance compared to the OMP scheme. Moreover, in the cases with high compressed ratio, the proposed algorithm can even outperform the benchmark performance achieved by the subspace programming and linear programming.en_US
dc.language.isoen_USen_US
dc.subjectCompressed sensingen_US
dc.subjectorthogonal matching pursuiten_US
dc.subjectK-besten_US
dc.titleA K-BEST ORTHOGONAL MATCHING PURSUIT FOR COMPRESSIVE SENSINGen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)en_US
dc.citation.spage5706en_US
dc.citation.epage5709en_US
dc.contributor.department電子工程學系及電子研究所zh_TW
dc.contributor.departmentDepartment of Electronics Engineering and Institute of Electronicsen_US
dc.identifier.wosnumberWOS:000329611505175-
Appears in Collections:Conferences Paper


Related Contents
Loading...