Model Reduction for Nonlinear Systems by Balanced Truncation of State and Gradient Covariance
DOI10.1137/22m1513228zbMath1520.65080arXiv2207.14387OpenAlexW4386930563MaRDI QIDQ6054284
Samuel E. Otto, Alberto Padovan, Clarence W. Rowley
Publication date: 27 September 2023
Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2207.14387
Grassmann manifoldkernel methodoblique projectionbalanced truncationadjoint methodactive subspacesdata-driven modelingmethod of snapshotsnonnormal systems
Large-scale problems in mathematical programming (90C06) Nonlinear systems in control theory (93C10) Iterative numerical methods for linear systems (65F10) Large-scale systems (93A15) Vector spaces, linear dependence, rank, lineability (15A03) Linear operators in reproducing-kernel Hilbert spaces (including de Branges, de Branges-Rovnyak, and other structured spaces) (47B32) Numerical methods for difference equations (65Q10)
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