Beamformers For Sparse Recovery
2013 (English)In: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New York: IEEE , 2013, 5920-5924 p.Conference paper (Refereed)
In sparse recovery from measurement data a common approach is to use greedy pursuit reconstruction algorithms. Most of these algorithms have a correlation filter for detecting active components in the sparse data. In this paper, we show how modifications can be made for the greedy pursuit algorithms so that they use beamformers insteadof the standard correlation filter. Using these beamformers, improved performance in the algorithms is obtained. In particular, we discuss beamformers for the average and worst case scenario and give methods for constructing them.
Place, publisher, year, edition, pages
New York: IEEE , 2013. 5920-5924 p.
, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, ISSN 1520-6149
Compressed sensing, Greedy pursuit algorithms, Beamforming
IdentifiersURN: urn:nbn:se:kth:diva-123993DOI: 10.1109/ICASSP.2013.6638800ISI: 000329611506015ScopusID: 2-s2.0-84890494911ISBN: 978-1-4799-0356-6OAI: oai:DiVA.org:kth-123993DiVA: diva2:651909
2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013; Vancouver, BC; Canada; 26 May 2013 through 31 May 2013
QC 201310222013-09-272013-06-242014-02-25Bibliographically approved