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)

Abstract

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
Pages343-347
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
Volume19
ISSN2219-5491

Conference

Conference19th European Signal Processing Conference, EUSIPCO 2011
Country/TerritorySpain
CityBarcelona
Period29/08/112/09/11

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