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AuthorElleuch, Ines
AuthorAbdelkefi, Fatma
AuthorSiala, Mohamed
AuthorHamila, Ridha
AuthorAl-Dhahir, Naofal
Available date2023-04-04T09:09:08Z
Publication Date2015
Publication Name2015 23rd European Signal Processing Conference, EUSIPCO 2015
ResourceScopus
URIhttp://dx.doi.org/10.1109/EUSIPCO.2015.7362675
URIhttp://hdl.handle.net/10576/41628
AbstractWe consider the problem of signal recovery under a sparsity prior, from multi-bit quantized compressed measurements. Recently, it has been shown that allowing a small fraction of the quantized measurements to saturate, combined with a saturation consistency recovery approach, would enhance reconstruction performance. In this paper, by leveraging the potential sparsity of the corrupting saturation noise, we propose a model-based greedy pursuit approach, where a cancel-then-recover procedure is applied in each iteration to estimate the unbounded sign-constrained saturation noise and remove it from the measurements to enable a clean signal estimate. Simulation results show the performance improvements of our proposed method compared with state-of-the-art recovery approaches, in the noiseless and noisy settings. 2015 EURASIP.
Languageen
PublisherIEEE
SubjectCancel-Then-Recover
Greedy Pursuit
Multi-Bit Quantized Compressed Sensing
Saturation
Sign Constraint
Sparse Corruptions
TitleOn quantized compressed sensing with saturated measurements via greedy pursuit
TypeConference Paper
Pagination1706-1710
dc.accessType Abstract Only


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