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This paper presents an educational platform developed to explore some concepts related to the relatively new signal acquisition paradigm known as Compressed Sensing (CS). CS aims to acquire a signal with sparse or compressible representation in a suitable domain, using a number of samples under the limit established by the Nyquist–Shannon sampling theorem. The application consists of a graphical user...
Compressed sensing is a recently proposed technique aiming to acquire a signal with sparse or compressible representation in some domain, using a number of samples under the limit established by the Nyquist theorem. The challenge is to recover the sensed signal solving an underdetermined linear system. Several techniques can be used for that purpose, such as l1 minimization, Greedy and combinatorial...
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