A physically-informed deep-learning model using time-reversal for locating a source from sparse and highly noisy sensors data
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Publication:2083682
DOI10.1016/j.jcp.2022.111592OpenAlexW4294631254MaRDI QIDQ2083682
Shai Dekel, Eli Turkel, Dan Givoli, Adar Kahana
Publication date: 11 October 2022
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jcp.2022.111592
Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems (65Mxx) Miscellaneous topics in partial differential equations (35Rxx) Waves in solid mechanics (74Jxx)
Related Items (3)
Multiscale extensions for enhancing coarse grid computations ⋮ Recovering source location, polarization, and shape of obstacle from elastic scattering data ⋮ Comparison of the FWI-Adjoint and Time Reversal Methods for the Identification of Elastic Scatterers
Uses Software
Cites Work
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