We are concerned with the inverse scattering problems associated with incomplete measurement data. It is a challenging topic of increasing importance in many practical applications. Based on a prototypical working model, we propose a machine learning based inverse scattering scheme, which integrates a CNN (convolution neural network) for the data retrieval. The proposed method can effectively cope with the reconstruction under limited-aperture and/or phaseless far-field data. Numerical experiments verify the promising features of our new scheme.
@article{arxiv.1910.12745,
title = {Machine learning based data retrieval for inverse scattering problems with incomplete data},
author = {Yu Gao and Kai Zhang},
journal= {arXiv preprint arXiv:1910.12745},
year = {2019}
}
Comments
The authors withdrew the previous three versions because more work was needed to furnish before its appearance as a formal paper. The current version is fine. All helpers agree with current version