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Fusion of Algorithms for Compressed Sensing
KTH, School of Electrical Engineering (EES), Communication Theory.ORCID iD: 0000-0003-2638-6047
2013 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 61, no 14, 3699-3704 p.Article in journal (Refereed) Published
Abstract [en]

For compressed sensing (CS), we develop a new scheme inspired by data fusion principles. In the proposed fusion based scheme, several CS reconstruction algorithms participate and they are executed in parallel, independently. The final estimate of the underlying sparse signal is derived by fusing the estimates obtained from the participating algorithms. We theoretically analyze this fusion based scheme and derive sufficient conditions for achieving a better reconstruction performance than any participating algorithm. Through simulations, we show that the proposed scheme has two specific advantages: 1) it provides good performance in a low dimensional measurement regime, and 2) it can deal with different statistical natures of the underlying sparse signals. The experimental results on real ECG signals shows that the proposed scheme demands fewer CS measurements for an approximate sparse signal reconstruction.

Place, publisher, year, edition, pages
2013. Vol. 61, no 14, 3699-3704 p.
Keyword [en]
Compressed sensing, data fusion, sparse signal reconstruction
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-125859DOI: 10.1109/TSP.2013.2259821ISI: 000321152800017Scopus ID: 2-s2.0-84880064779OAI: oai:DiVA.org:kth-125859DiVA: diva2:641254
Note

QC 20130816

Available from: 2013-08-16 Created: 2013-08-15 Last updated: 2017-12-06Bibliographically approved

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Chatterjee, Saikat

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