AIMS Mathematics (Apr 2024)
Shape reconstruction of acoustic obstacle with linear sampling method and neural network
Abstract
We consider the inverse scattering problem of reconstructing the boundary of an obstacle by using far-field data. With the plane wave as the incident wave, a priori information of the impenetrable obstacle can be obtained via the linear sampling method. We have constructed the shape parameter inversion model based on a neural network to reconstruct the obstacle. Numerical experimental results demonstrate that the model proposed in this paper is robust and performs well with a small number of observation directions.
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