Reduced look ahead orthogonal matching pursuit
2014 (English)In: 2014 20th National Conference on Communications, NCC 2014, IEEE Computer Society, 2014, 6811329- p.Conference paper (Refereed)
Compressed Sensing (CS) is an elegant technique to acquire signals and reconstruct them efficiently by solving a system of under-determined linear equations. The excitement in this field stems from the fact that we can sample at a rate way below the Nyquist rate and still reconstruct the signal provided some conditions are met. Some of the popular greedy reconstruction algorithms are the Orthogonal Matching Pursuit (OMP), the Subspace Pursuit (SP) and the Look Ahead Orthogonal Matching Pursuit (LAOMP). The LAOMP performs better than the OMP. However, when compared to the SP and the OMP, the computational complexity of LAOMP is higher. We introduce a modified version of the LAOMP termed as Reduced Look Ahead Orthogonal Matching Pursuit (Reduced LAOMP). Reduced LAOMP uses prior information from the results of the OMP and the SP in the quest to speedup the look ahead strategy in the LAOMP. Monte Carlo simulations of this algorithm deliver promising results.
Place, publisher, year, edition, pages
IEEE Computer Society, 2014. 6811329- p.
Compressed Sensing, Greedy reconstruction, Matching Pursuit
IdentifiersURN: urn:nbn:se:kth:diva-146788DOI: 10.1109/NCC.2014.6811329ISI: 000355320700092ScopusID: 2-s2.0-84901440395ISBN: 978-1-4799-2361-8OAI: oai:DiVA.org:kth-146788DiVA: diva2:725699
2014 20th National Conference on Communications, NCC 2014, Kanpur, India, 28 February 2014 through 2 March 2014
QC 201406172014-06-172014-06-162015-06-25Bibliographically approved