Greedy pursuits for compressed sensing of jointly sparse signals
2011 (English)In: European Signal Processing Conference, European Association for Signal and Image Processing, 2011, p. 368-372Conference paper, Published paper (Refereed)
Abstract [en]
For compressed sensing with jointly sparse signals, we present a new signal model and two new joint iterativegreedy-pursuit recovery algorithms. The signal model is based on the assumption of a jointly shared support-set and the joint recovery algorithms have knowledge of the size of the shared support-set. Through experimental evaluation, we show that the new joint algorithms provide significant performance improvements compared to regular algorithms which do not exploit a joint sparsity.
Place, publisher, year, edition, pages
European Association for Signal and Image Processing, 2011. p. 368-372
Series
European Signal Processing Conference, ISSN 2219-5491
Keywords [en]
Compressive sensing, Experimental evaluation, Joint algorithms, Joint sparsity, Performance improvements, Recovery algorithms, Signal models, Sparse signals, Signal reconstruction, Algorithms
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-149791ISI: 000377963100075Scopus ID: 2-s2.0-84863767947OAI: oai:DiVA.org:kth-149791DiVA, id: diva2:741639
Conference
19th European Signal Processing Conference, EUSIPCO 2011; Barcelona, Spain, 29 August 2011 - 2 September 2011
Note
QC 20140828
2014-08-282014-08-272022-06-23Bibliographically approved