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Paper detail

Target Identification Using Dictionary Matching of Generalized Polarization Tensors

The aim of this paper is to provide a fast and efficient procedure for (real-time) target identification in imaging based on matching on a dictionary of precomputed generalized polarization tensors (GPTs). The approach is based on some important properties of the GPTs and new invariants. A new shape representation is given and numerically tested in the presence of measurement noise. The stability and resolution of the proposed identification algorithm is numerically quantified.

preprint2013arXivOpen access
Habib AmmariThomas BoulierJosselin GarnierWenjia JingHyœnbæ KangHan Wang
math.APmath.OCmath-phmath.MPmath.NA
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Habib AmmariThomas BoulierJosselin GarnierWenjia JingHyœnbæ KangHan Wang

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