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Recovery of Binary Sparse Signals From Compressed Linear Measurements via Polynomial Optimization | IEEE Journals & Magazine | IEEE Xplore

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


Abstract:

The recovery of signals with finite-valued components from few linear measurements is a problem with widespread applications and interesting mathematical characteristics....Show More

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 compressed 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.
Published in: IEEE Signal Processing Letters ( Volume: 26, Issue: 7, July 2019)
Page(s): 1070 - 1074
Date of Publication: 30 May 2019

ISSN Information:


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