The relative root-mean-square error of finite-dimensional Koopman Control Family predictors is strictly upper-bounded by the square root of the largest eigenvalue of the newly defined control forward-backward consistency matrix.
Temporal forward-backward consistency, not residual error, measures the prediction accuracy of Extended Dynamic Mode Decomposition
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A hybrid principal-vector pruning method is proposed to refine invariant subspaces for Koopman approximations, supported by error bounds on eigenfunction retention and a rank-one update scheme for efficient computation.
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Subspace Pruning via Principal Vectors for Accurate Koopman-Based Approximations
A hybrid principal-vector pruning method is proposed to refine invariant subspaces for Koopman approximations, supported by error bounds on eigenfunction retention and a rank-one update scheme for efficient computation.