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. 

العنوان

IEEE Signal Processing Letters

الناشر

IEEE Signal Processing Letters

بلد الناشر

الولايات المتحدة الأمريكية

Indexing

Scopus

معامل التأثير

None

نوع المنشور

Both (Printed and Online)

المجلد

26

السنة

2019

الصفحات

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