Hybrid greedy pursuit

Saikat Chatterjee, Dennis Sundman, Mikko Vehkaperä, Mikael Skoglund

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

2 Citations (Scopus)


For constructing the support set of a sparse vector in the standard compressive sensing framework, we develop a hybrid greedy pursuit algorithm that combines the advantages of serial and parallel atom selection strategies. In an iterative framework, the hybrid algorithm uses a joint sparsity information extracted from the independent use of serial and parallel greedy pursuit algorithms. Through experimental evaluations, the hybrid algorithm is shown to provide a significant improvement for the support set recovery performance.

Original languageEnglish
Title of host publication19th European Signal Processing Conference, EUSIPCO 2011
PublisherIEEE Institute of Electrical and Electronic Engineers
Number of pages5
Publication statusPublished - 1 Dec 2011
MoE publication typeA4 Article in a conference publication
Event19th European Signal Processing Conference, EUSIPCO 2011 - Barcelona, Spain
Duration: 29 Aug 20112 Sept 2011

Publication series

SeriesEuropean Signal Processing Conference


Conference19th European Signal Processing Conference, EUSIPCO 2011


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