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Library-learning-assisted robust principal component analysis for denoising severely corrupted flow fields

Koop, Pablo et al.
arXiv (All) · Papers
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data-analysisfluid-dynamicsstatistics-and-probability
Large-amplitude entrywise corruption can distort flow-field data and contaminate extracted modes. Robust principal component analysis (RPCA) separates low-rank flow content from a sparse corruption component, but recovery deteriorates when corruption occupies a large fraction of measurements. We int
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