Sensing matrix sensitivity to random Gaussian perturbations in compressed sensing
Lavrenko A, Römer F, Galdo GD, Thomä RS (2018)
Publication Type: Conference contribution
Publication year: 2018
Publisher: European Signal Processing Conference, EUSIPCO
Book Volume: 2018-September
Pages Range: 583-587
Conference Proceedings Title: European Signal Processing Conference
Event location: Rome, ITA
ISBN: 9789082797015
DOI: 10.23919/EUSIPCO.2018.8553575
Abstract
In compressed sensing, the choice of the sensing matrix plays a crucial role: it defines the required hardware effort and determines the achievable recovery performance. Recent studies indicate that by optimizing a sensing matrix, one can potentially improve system performance compared to random ensembles. In this work, we analyze the sensitivity of a sensing matrix design to random perturbations, e.g., caused by hardware imperfections, with respect to the total (average) matrix coherence. We derive an exact expression for the average deterioration of the total coherence in the presence of Gaussian perturbations as a function of the perturbations' variance and the sensing matrix itself. We then numerically evaluate the impact it has on the recovery performance.
Involved external institutions
Germany (DE)How to cite
APA:
Lavrenko, A., Römer, F., Galdo, G.D., & Thomä, R.S. (2018). Sensing matrix sensitivity to random Gaussian perturbations in compressed sensing. In European Signal Processing Conference (pp. 583-587). Rome, ITA: European Signal Processing Conference, EUSIPCO.
MLA:
Lavrenko, Anastasia, et al. "Sensing matrix sensitivity to random Gaussian perturbations in compressed sensing." Proceedings of the 26th European Signal Processing Conference, EUSIPCO 2018, Rome, ITA European Signal Processing Conference, EUSIPCO, 2018. 583-587.
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