Analyzing Nonlinear Dynamics via Data-Driven Dynamic Mode Decomposition-Like Methods
This article presents a review on two methods based on dynamic mode decomposition and its multiple applications, focusing on higher order dynamic mode decomposition (which provides a purely temporal Fourier-like decomposition) and spatiotemporal Koopman decomposition (which gives a spatiotemporal Fo...
Saved in:
Main Authors: | Soledad Le Clainche, José M. Vega |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2018-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2018/6920783 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A novel data augmentation tool for enhancing machine learning classification: A new application of the higher order dynamic mode decomposition for improved cardiac disease identification
by: Nourelhouda Groun, et al.
Published: (2025-03-01) -
Forecasting long-time dynamics in quantum many-body systems by dynamic mode decomposition
by: Ryui Kaneko, et al.
Published: (2025-01-01) -
Assessing Nonlinear Dynamics and Trends in Precipitation by Ensemble Empirical Mode Decomposition (EEMD) and Fractal Approach in Benin Republic (West Africa)
by: Médard Noukpo Agbazo, et al.
Published: (2021-01-01) -
Using the Nonuniform Dynamic Mode Decomposition to Reduce the Storage Required for PDE Simulations
by: Brenton T. Hall, et al.
Published: (2019-01-01) -
Nonlinear Langevin dynamics via holography
by: Bidisha Chakrabarty, et al.
Published: (2020-01-01)