On quantized compressed sensing with saturated measurements via greedy pursuit
Author | Elleuch, Ines |
Author | Abdelkefi, Fatma |
Author | Siala, Mohamed |
Author | Hamila, Ridha |
Author | Al-Dhahir, Naofal |
Available date | 2023-04-04T09:09:08Z |
Publication Date | 2015 |
Publication Name | 2015 23rd European Signal Processing Conference, EUSIPCO 2015 |
Resource | Scopus |
Abstract | We 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. |
Language | en |
Publisher | IEEE |
Subject | Cancel-Then-Recover Greedy Pursuit Multi-Bit Quantized Compressed Sensing Saturation Sign Constraint Sparse Corruptions |
Type | Conference Paper |
Pagination | 1706-1710 |
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Electrical Engineering [2611 items ]