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- W3104292953 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 work, 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." @default.
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- W3104292953 date "2019-07-01" @default.
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- W3104292953 title "Recovery of Binary Sparse Signals From Compressed Linear Measurements via Polynomial Optimization" @default.
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- W3104292953 doi "https://doi.org/10.1109/lsp.2019.2919943" @default.
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