Extracting the latent underlying structures of complex nonlinear local and nonlocal flows is essential for their analysis and modeling. In this Element the authors attempt to provide a consistent framework through Koopman theory and its related popular discrete approximation - dynamic mode decomposition (DMD).
Extracting the latent underlying structures of complex nonlinear local and nonlocal flows is essential for their analysis and modeling. In this Element the authors attempt to provide a consistent framework through Koopman theory and its related popular discrete approximation - dynamic mode decomposition (DMD).
Produktdetails
Produktdetails
Elements in Non-local Data Interactions: Foundations and Applications
1. Introduction 2. Preliminaries 3. Motivation for This Work 4. Koopman Eigenfunctions and Modes 5. Koopman Theory for Partial Differential Equation 6. Mode Decomposition Based on Time State-Space Mapping 7. Examples 8. Conclusion List of Symbols List of Abbreviations Appendix A Extended Dynamic Mode Decomposition Induced from Inverse Mapping Appendix B Sparse Representation References.
1. Introduction 2. Preliminaries 3. Motivation for This Work 4. Koopman Eigenfunctions and Modes 5. Koopman Theory for Partial Differential Equation 6. Mode Decomposition Based on Time State-Space Mapping 7. Examples 8. Conclusion List of Symbols List of Abbreviations Appendix A Extended Dynamic Mode Decomposition Induced from Inverse Mapping Appendix B Sparse Representation References.
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