Corpus ID: 235694168

Learned Global Optimization for Inverse Scattering Problems - Matching Global Search with Computational Efficiency

@article{Salucci2021LearnedGO,
  title={Learned Global Optimization for Inverse Scattering Problems - Matching Global Search with Computational Efficiency},
  author={Marco Salucci and Lorenzo Poli and Paolo Rocca and Andrea Massa},
  journal={ArXiv},
  year={2021},
  volume={abs/2107.00332}
}
The computationally-efficient solution of fully non-linear microwave inverse scattering problems (ISPs) is addressed. An innovative System-by-Design (SbD) based method is proposed to enable, for the first time to the best of the authors’ knowledge, an effective, robust, and time-efficient exploitation of an evolutionary algorithm (EA) to perform the global minimization of the data-mismatch cost function. According to the SbD paradigm as suitably applied to ISPs, the proposed approach founds on… Expand

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