Dictionary learning for Kernel EDMD
Studying nonlinear dynamical systems through their state space behavior can be challenging, and one possible alternative is to analyze them via their associated Koopman operator. This turns the nonlinear problem into a linear, infinite-dimensional one. To approximate the operator in finite dimensions, extended dynamic mode decomposition (EDMD) is a commonly used algorithm. It requires a finite list of functionals and a set of snapshots from the system to compute an approximation of the operator and its corresponding spectrum. Instead of choosing the list of functionals directly, it can be implicitly defined via kernels, a method known as kernel extended dynamic mode decomposition (kEDMD)....
| Authors | Erik Lien Bolager, Boumediene Hamzi, Houman Owhadi et al. |
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| Primary category | math.DS |
| Published | 28 April 2026 |
| Last updated at source | 14 October 2026 |
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