Math @ Duke
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Publications [#235774] of Robert Calderbank
Papers Published
- Wang, M; Xu, W; Calderbank, R, Compressed sensing with corrupted participants,
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
(October, 2013),
pp. 4653-4657, IEEE, ISSN 1520-6149 [doi]
(last updated on 2025/02/21)
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. © 2013 IEEE.
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