The work formulates a sparsity-promoting inverse problem for source identification in tomographic sensing of chemical plumes using level-set representations of concentration thresholds.
A generalized probabilistic learning approach for multi-fidelity uncertainty quantification in complex physical simulations
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Sparsity-Driven Source Localization in Tomographic Sensing Applications
The work formulates a sparsity-promoting inverse problem for source identification in tomographic sensing of chemical plumes using level-set representations of concentration thresholds.