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· 2004 · DOI 10.1002/mds.20115

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physics.data-an 1

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2026 1

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CONDITIONAL 1

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Inferring Non-Normal Amplification Geometry from Multivariate Time Series

physics.data-an · 2026-07-16 · conditional · novelty 6.0

A moving-window ridge-regression pipeline fits local linear operators, extracts a dominant 2D input-response plane by optimization or commutator methods, and tracks R = K/Kc(Δ), recovering this reduced non-normal geometry from finite multivariate time series with far fewer samples than full operator

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  • Inferring Non-Normal Amplification Geometry from Multivariate Time Series physics.data-an · 2026-07-16 · conditional · none · ref 24

    A moving-window ridge-regression pipeline fits local linear operators, extracts a dominant 2D input-response plane by optimization or commutator methods, and tracks R = K/Kc(Δ), recovering this reduced non-normal geometry from finite multivariate time series with far fewer samples than full operator