Compressive Sensing for Inverse Scattering
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Compressive sensing is a new field in signal processing and applied mathematics. It allows one to simultaneously sample and compress signals which are known to have a sparse representation in a known basis or dictionary along with the subsequent recovery by linear programming (requiring polynomial (P) time) of the original signals with low or no error [1–3]. Compressive measurements or samples are non-adaptive, possibly random linear projections
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Compressive sensing is a new field in signal processing and applied mathematics. It allows one to simultaneously sample and compress signals which are known to have a sparse representation in a known basis or dictionary along with the subsequent recovery by linear programming (requiring polynomial (P) time) of the original signals with low or no error [1–3]. Compressive measurements or samples are non-adaptive, possibly random linear projections
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inverse scattering, signal processing, random linear projection, applied mathematics, compressive measurement, sparse representation, new field, known basis, compressive sensing, original signal, linear programming, subsequent recovery, compress signal , inverse scattering, signal processing, random linear projection, applied mathematics, compressive measurement, sparse representation, new field, known basis, compressive sensing, original signal, linear programming, subsequent recovery, compress signal