Conference proceeding
Compressed sensing with corrupted participants
2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.4653-4657
05/2013
DOI: 10.1109/ICASSP.2013.6638542
Abstract
Compressed sensing (CS) theory promises one can recover real-valued sparse signal from a small number of linear measurements. Motivated by network monitoring with link failures, we for the first time consider the problem of recovering signals that contain both real-valued entries and corruptions, where the real entries represent transmission delays on normal links and the corruptions represent failed links. Unlike conventional CS, here a measurement is real-valued only if it does not include a failed link, and it is corrupted otherwise. We prove that O((d + 1)max(d, k) log n) nonadaptive measurements are enough to recover all n-dimensional signals that contain k nonzero real entries and d corruptions. We provide explicit constructions of measurements and recovery algorithms. We also analyze the performance of signal recovery when the measurements contain errors.
Details
- Title: Subtitle
- Compressed sensing with corrupted participants
- Creators
- Meng Wang - Rensselaer Polytechnic InstituteWeiyu Xu - University of IowaRobert Calderbank - Duke University
- Resource Type
- Conference proceeding
- Publication Details
- 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.4653-4657
- Publisher
- IEEE
- DOI
- 10.1109/ICASSP.2013.6638542
- ISSN
- 1520-6149
- eISSN
- 2379-190X
- Language
- English
- Date published
- 05/2013
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984197432802771
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