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Compressive sensing (CS) is currently one the most active research fields in information engineering and science. The flexibility, robustness, accuracy, effectiveness, and sound theory behind such a paradigm have motivated a great interest in developing and applying CS to many domains, including inverse scattering. Unfortunately, electromagnetic imaging problems have some unique theoretical features that prevent a straightforward exploitation of CS tools. Therefore, suitable CS-based strategies must be considered in such a framework.
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Oliveri et al. (2017) studied this question.
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