Transform & Learn: A data-driven approach to nonlinear model reduction
Author:
Affiliation:
1. Massachusetts Institute of Technology
2. University of Texas, Austin
Publisher
American Institute of Aeronautics and Astronautics
Reference47 articles.
1. Approximation of Large-Scale Dynamical Systems
2. A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems
3. Nonlinear Model Order Reduction via Lifting Transformations and Proper Orthogonal Decomposition
4. Two-Sided Projection Methods for Nonlinear Model Order Reduction
5. Optimal control of vortex shedding using low-order models. Part I?open-loop model development
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