Pregled bibliografske jedinice broj: 696896
Reconstruction of sparse signals from highly corrupted measurements by nonconvex minimization
Reconstruction of sparse signals from highly corrupted measurements by nonconvex minimization // Proceedings of the 2014 IEEE International Conference on ACoustics, Speech and Signal Processing (ICASSP)
Firenca, Italija: Institute of Electrical and Electronics Engineers (IEEE), 2014. str. 3395-3399 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
Reconstruction of sparse signals from highly corrupted measurements by nonconvex minimization
Autori
Filipović, Marko
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 2014 IEEE International Conference on ACoustics, Speech and Signal Processing (ICASSP)
/ - : Institute of Electrical and Electronics Engineers (IEEE), 2014, 3395-3399
Skup
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Mjesto i datum
Firenca, Italija, 05.05.2014. - 09.05.2014
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Compressive Sensing ; Sparse Signal Reconstruction ; Nonconvex Optimization ; Restricted Isometry
Sažetak
We propose a method for signal recovery in compressed sensing when measurements can be highly corrupted. It is based on lp minimization for 0 < p <= 1. Since it was shown that lp minimization performs better than l1 minimization when there are no large errors, the proposed approach is a natural extension to compressed sensing with corruptions. We provide a theoretical justification of this idea, based on analogous reasoning as in the case when measurements are not corrupted by large errors. Better performance of the proposed approach compared to l1 minimization is illustrated in numerical experiments.
Izvorni jezik
Engleski
