Universal algorithm for compressive sampling
2015 (English)In: 2015 23rd European Signal Processing Conference, EUSIPCO 2015, Institute of Electrical and Electronics Engineers (IEEE), 2015, 689-693 p.Conference paper (Refereed)Text
In a standard compressive sampling (CS) setup, we develop a universal algorithm where multiple CS reconstruction algorithms participate and their outputs are fused to achieve a better reconstruction performance. The new method is called universal algorithm for CS (UACS) that is iterative in nature and has a restricted isometry property (RIP) based theoretical convergence guarantee. It is shown that if one participating algorithm in the design has a converging recurrence inequality relation then the UACS also holds a converging recurrence inequality relation over iterations. An example of the UACS is presented and studied through simulations for demonstrating its flexibility and performance improvement.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2015. 689-693 p.
Compressive sampling, greedy algorithms, iterative fusion, restricted isometry property, Compressed sensing, Iterative methods, Matrix algebra, Signal processing, Reconstruction algorithms, Restricted isometry properties, Restricted isometry properties (RIP), Universal algorithm, Algorithms
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:kth:diva-186793DOI: 10.1109/EUSIPCO.2015.7362471ISI: 000377943800139ScopusID: 2-s2.0-84963961479ISBN: 9780992862633OAI: oai:DiVA.org:kth-186793DiVA: diva2:938612
23rd European Signal Processing Conference, EUSIPCO 2015, 31 August 2015 through 4 September 2015
QC 201606172016-06-172016-05-132016-07-18Bibliographically approved