Ambat, Sooraj K and Chatterjee, Saikat and Hari, KVS (2013) Fusion of algorithms for compressed sensing. In: IEEE Transactions on Signal Processing, 61 (14). pp. 3699-3704.
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Abstract
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.
Item Type: | Journal Article |
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Publication: | IEEE Transactions on Signal Processing |
Publisher: | IEEE-Institute of Electrical and Electronics Engineers Inc |
Additional Information: | Copyright of this article belongs to IEEE-Institute of Electrical and Electronics Engineers Inc. |
Keywords: | Compressed Sensing; Data Fusion; Sparse Signal Reconstruction |
Department/Centre: | Division of Electrical Sciences > Electrical Communication Engineering |
Date Deposited: | 19 Sep 2013 17:32 |
Last Modified: | 19 Sep 2013 17:32 |
URI: | http://eprints.iisc.ac.in/id/eprint/47213 |
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