lcHOSVD reconstructs 3D velocity and pollutant fields from 1-4% sensor locations, achieving lower errors than matrix-based lcSVD when multidimensional coupling is strong and greater robustness to uneven sensor placement.
Ensemble kalman filter for data assimilation coupled with low-resolution computations techniques applied in fluid dynamics,
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Low-Cost High-Order Singular Value Decomposition for Tensor-Based Reconstruction from Sparse Sensor Measurements: Urban Flow and Air-Quality Applications
lcHOSVD reconstructs 3D velocity and pollutant fields from 1-4% sensor locations, achieving lower errors than matrix-based lcSVD when multidimensional coupling is strong and greater robustness to uneven sensor placement.