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arXiv · 2002.04375

Generalized Kernel-Based Dynamic Mode Decomposition

Patrick Heas·Cedric Herzet·Benoit Combes
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Abstract

Reduced modeling in high-dimensional reproducing kernel Hilbert spaces offers the opportunity to approximate efficiently non-linear dynamics. In this work, we devise an algorithm based on low rank constraint optimization and kernel-based computation that generalizes a recent approach called "kernel-based dynamic mode decomposition". This new algorithm is characterized by a gain in approximation accuracy, as evidenced by numerical simulations, and in computational complexity.

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Patrick Heas, Cedric Herzet, Benoit Combes. 2020-02-11. Generalized Kernel-Based Dynamic Mode Decomposition. https://arxiv.org/abs/2002.04375

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