The recovery of signals with finite-valued components from few linear measurements is a problem with widespread applications and interesting mathematical characteristics. In the com-pressed sensing framework, tailored methods have been recently proposed to deal with the case of finite-valued sparse signals. In this letter, we focus on binary sparse signals and we propose a novel formulation, based on polynomial optimization. This approach is analyzed and compared to the state-of-the-art binary compressed sensing methods.

Recovery of Binary Sparse Signals From Compressed Linear Measurements via Polynomial Optimization / Fosson, Sophie Marie; Abuabiah, Mohammad. - In: IEEE SIGNAL PROCESSING LETTERS. - ISSN 1070-9908. - 26:7(2019), pp. 1070-1074. [10.1109/LSP.2019.2919943]

Recovery of Binary Sparse Signals From Compressed Linear Measurements via Polynomial Optimization

Fosson, Sophie Marie;Abuabiah, Mohammad
2019

Abstract

The recovery of signals with finite-valued components from few linear measurements is a problem with widespread applications and interesting mathematical characteristics. In the com-pressed sensing framework, tailored methods have been recently proposed to deal with the case of finite-valued sparse signals. In this letter, we focus on binary sparse signals and we propose a novel formulation, based on polynomial optimization. This approach is analyzed and compared to the state-of-the-art binary compressed sensing methods.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2739552
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