Reduced Order Model Approach to Inverse Scattering
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Publication:3296461
DOI10.1137/19M1296355zbMath1441.65073arXiv1910.13014OpenAlexW3022440915WikidataQ118126685 ScholiaQ118126685MaRDI QIDQ3296461
Vladimir Druskin, Mikhail Zaslavsky, Alexander V. Mamonov, Liliana Borcea, Jörn Zimmerling
Publication date: 7 July 2020
Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1910.13014
Approximation by rational functions (41A20) Numerical methods for inverse problems for initial value and initial-boundary value problems involving PDEs (65M32)
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On extension of the data driven ROM inverse scattering framework to partially nonreciprocal arrays ⋮ Numerical wave propagation aided by deep learning ⋮ Waveform Inversion with a Data Driven Estimate of the Internal Wave ⋮ Computational inverse problems for partial differential equations. Abstracts from the workshop held December 6--12, 2020 (hybrid meeting) ⋮ A reduced order model approach to inverse scattering in lossy layered media ⋮ Lippmann–Schwinger–Lanczos algorithm for inverse scattering problems ⋮ Reduced order model approach for imaging with waves
Cites Work
- Linearized inverse scattering problems in acoustics and elasticity
- Robust nonlinear processing of active array data in inverse scattering via truncated reduced order models
- Direct, Nonlinear Inversion Algorithm for Hyperbolic Problems via Projection-Based Model Reduction
- Fundamentals of Radar Imaging
- The seismic reflection inverse problem
- Inverse problems in ocean acoustics
- Untangling the nonlinearity in inverse scattering with data-driven reduced order models
- A Nonlinear Method for Imaging with Acoustic Waves Via Reduced Order Model Backprojection
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