A hybrid principal-vector pruning framework refines Koopman subspace invariance with error bounds and rank-one update efficiency for lifted linear prediction.
A data-driven approximation of the Koopman operator: Extending dynamic mode decomposition,
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Subspace Pruning via Principal Vectors for Accurate Koopman-Based Approximations
A hybrid principal-vector pruning framework refines Koopman subspace invariance with error bounds and rank-one update efficiency for lifted linear prediction.