We propose a new approach for the recovery of binary signals in compressed sensing, based on the local minimization of a non-convex cost functional. The desired signal is proved to be a local minimum of the functional under mild conditions on the sensing matrix and on the number of measurements. We develop a procedure to achieve the desired local minimum, and, finally, we propose numerical experiments that show the improvement obtained by the proposed approach with respect to classical convex methods.

Non-convex approach to binary compressed sensing / Fosson, Sophie M.. - 2018-:(2019), pp. 1959-1963. (Intervento presentato al convegno 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018 tenutosi a Asilomar, CA, USA nel 2018) [10.1109/ACSSC.2018.8645293].

Non-convex approach to binary compressed sensing

Fosson, Sophie M.
2019

Abstract

We propose a new approach for the recovery of binary signals in compressed sensing, based on the local minimization of a non-convex cost functional. The desired signal is proved to be a local minimum of the functional under mild conditions on the sensing matrix and on the number of measurements. We develop a procedure to achieve the desired local minimum, and, finally, we propose numerical experiments that show the improvement obtained by the proposed approach with respect to classical convex methods.
2019
9781538692189
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2729893
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