FUSION OF ALGORITHMS FOR COMPRESSED SENSING

Ambat, Sooraj K and Chatterjee, Saikat and Hari, KVS (2013) FUSION OF ALGORITHMS FOR COMPRESSED SENSING. In: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), MAY 26-31, 2013, Vancouver, CANADA, pp. 5860-5864.

PDF ieee_int_con_aco_spe_sin_pro_5860_2013.pdf - Published Version Restricted to Registered users only Download (164kB) | Request a copy

Abstract

Numerous algorithms have been proposed recently for sparse signal recovery in Compressed Sensing (CS). In practice, the number of measurements can be very limited due to the nature of the problem and/or the underlying statistical distribution of the non-zero elements of the sparse signal may not be known a priori. It has been observed that the performance of any sparse signal recovery algorithm depends on these factors, which makes the selection of a suitable sparse recovery algorithm difficult. To take advantage in such situations, we propose to use a fusion framework using which we employ multiple sparse signal recovery algorithms and fuse their estimates to get a better estimate. Theoretical results justifying the performance improvement are shown. The efficacy of the proposed scheme is demonstrated by Monte Carlo simulations using synthetic sparse signals and ECG signals selected from MIT-BIH database.

Item Type:	Conference Proceedings
Series.:	International Conference on Acoustics Speech and Signal Processing ICASSP
Publisher:	IEEE
Additional Information:	Copyright for this article belongs to the IEEE, USA
Keywords:	Compressed Sensing; Fusion; Sparse Recovery; Support Recovery; Signal Reconstruction
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering > Electrical Communication Engineering - Technical Reports
Date Deposited:	04 Mar 2014 11:36
Last Modified:	04 Mar 2014 11:36
URI:	http://eprints.iisc.ac.in/id/eprint/48486

Actions (login required)

View Item