Recovery of Binary Sparse Signals From Compressed Linear Measurements via Polynomial Optimization
Recovery of Binary Sparse Signals From Compressed Linear Measurements via Polynomial Optimization
复制标题
通过多项式优化从压缩线性测量中恢复二进制稀疏信号
DOI：
10.1109/lsp.2019.2919943
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发表时间：
2019
影响因子：
3.9
通讯作者：
Mohammad Abuabiah
中科院分区：
文献类型：
--
作者：
S. Fosson;Mohammad Abuabiah
从少量的线性测量中恢复具有有限值分量的信号是一个具有广泛应用和有趣的数学特性的问题。在压缩感知框架中，最近已经提出了定制的方法来处理有限值稀疏信号的情况。在这封信中，我们重点关注二进制稀疏信号，并提出了一种基于多项式优化的新公式。这种方法进行了分析和比较，最先进的二进制压缩传感方法。
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.