A physics-informed boundary integral network learns boundary pressure from microphone measurements and reconstructs the interior sound field, outperforming PINN and PIDL baselines in simulated rooms.
Sparse Representation of a Spatial Sound Field in a Reverberant Environment,
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Sound Field Reconstruction Using Physics-Informed Boundary Integral Networks
A physics-informed boundary integral network learns boundary pressure from microphone measurements and reconstructs the interior sound field, outperforming PINN and PIDL baselines in simulated rooms.