English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The computationally efficient solution of fully nonlinear 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&#x2019; 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 is found on: 1) a smart reformulation of the ISP based on the <italic>a priori</italic> information on the imaged targets for defining a minimum dimensionality and representative set of degrees of freedom (DoFs) and 2) the artificial intelligence (AI)-driven integration of a customized global search technique with a digital twin (DT) predictor based on the Gaussian process (GP) theory. Representative numerical and experimental results are provided to assess the effectiveness and the efficiency of the proposed approach also in comparison with competitive state-of-the-art inversion techniques.

Learned Global Optimization for Inverse Scattering Problems: Matching Global Search With Computational Efficiency