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EnglishWe consider the problem of the recovery of a k-sparse vector from compressed linear measurements when data are corrupted by a quantization noise. When the number of measurements is not sufficiently large, different k-sparse solutions may be present in the feasible set, and the classical `1 approach may be unsuccessful. For this motivation, we propose a non-convex quadratic programming method, which exploits prior information on the magnitude of the non-zero parameters. This results in a more efficient support recovery. We provide sufficient conditions for successful recovery and numerical simulations to illustrate the practical feasibility of the proposed method.
Sparse linear regression with compressed and low-precision data via concave quadratic programming / CERONE, VITO; FOSSON, SOPHIE; REGRUTO TOMALINO, DIEGO. - (2019), pp. 6971-6976. ((Intervento presentato al convegno IEEE Conference on Decision and Control (CDC) tenutosi a Nice (France) nel 11-13 Dicembre 2019.
| Titolo: | Sparse linear regression with compressed and low-precision data via concave quadratic programming |
| Autori: | |
| Data di pubblicazione: | 2019 |
| Abstract: | We consider the problem of the recovery of a k-sparse vector from compressed linear measurements ...when data are corrupted by a quantization noise. When the number of measurements is not sufficiently large, different k-sparse solutions may be present in the feasible set, and the classical `1 approach may be unsuccessful. For this motivation, we propose a non-convex quadratic programming method, which exploits prior information on the magnitude of the non-zero parameters. This results in a more efficient support recovery. We provide sufficient conditions for successful recovery and numerical simulations to illustrate the practical feasibility of the proposed method. |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| 1909.03705.pdf | Articolo | 2. Post-print / Author's Accepted Manuscript | PUBBLICO - Tutti i diritti riservati | Visibile a tuttiVisualizza/Apri |
| 09030257.pdf | 2a Post-print versione editoriale / Version of Record | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia |
http://hdl.handle.net/11583/2785501
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