- Fast data|driven model reduction for nonlinear dynamical systems🔍
- Rapid data|driven model reduction of nonlinear dynamical systems ...🔍
- haller|group/SSMLearn🔍
- Data|driven modeling and prediction of non|linearizable dynamics ...🔍
- Data|driven Nonlinear Model Reduction using Koopman Theory🔍
- Nonlinear Reduced|Order Modeling from Data by Prof. George Haller.🔍
- What is data|driven model reduction🔍
- Data|driven nonlinear model reduction to spectral submanifolds in ...🔍
Fast data|driven model reduction for nonlinear dynamical systems
Fast data-driven model reduction for nonlinear dynamical systems
Due to its explicit coefficient fitting, fastSSM achieves a major speedup, and enables analysis of significantly higher-dimensional data than ...
Fast data-driven model reduction for nonlinear dynamical systems
We present a fast method for nonlinear data-driven model reduction of dynamical systems onto their slowest nonresonant spectral submanifolds (SSMs).
Fast data-driven model reduction for nonlinear dynamical systems
Correction to: Fast data-driven model reduction for nonlinear dynamical systems ... Avoid common mistakes on your manuscript. ... The article was ...
Rapid data-driven model reduction of nonlinear dynamical systems ...
Rapid data-driven model reduction of nonlinear dynamical systems including chemical reaction networks using ℓ1-regularization ... Large-scale ...
haller-group/SSMLearn: Data-driven reduced order modeling for ...
J. Axås, M. Cenedese & G. Haller, Fast data-driven model reduction for nonlinear dynamical systems, Nonlinear Dynamics 111 (2023) 7941–7957 ...
Data-driven modeling and prediction of non-linearizable dynamics ...
Our data-driven, sparse, nonlinear models are obtained as extended normal forms of the reduced dynamics on low-dimensional, attracting spectral ...
Fast data-driven model reduction for nonlinear dynamical systems
AbstractWe present a fast method for nonlinear data-driven model reduction of dynamical systems onto their slowest nonresonant spectral submanifolds (SSMs).
Data-driven Nonlinear Model Reduction using Koopman Theory
We use Koopman theory for data-driven model reduction of nonlinear dynamical systems with controls. We propose generic model structures combining delay- ...
Rapid data-driven model reduction of nonlinear dynamical systems ...
Large-scale nonlinear dynamical systems, such as models of atmospheric hydrodynamics, chemical reaction networks, and electronic circuits, often involve ...
Nonlinear Reduced-Order Modeling from Data by Prof. George Haller.
... dynamical-systems-based alternative to machine learning in the data-driven reduced-order modeling of nonlinear phenomena. Specifically ...
What is data-driven model reduction - Karen E. Willcox
Our data-driven model reduction techniques apply to general linear and nonlinear problems. In the linear setting, our (dynamic) data-driven reduced models rely ...
Data-driven nonlinear model reduction to spectral submanifolds in ...
Fast data-driven model reduction for nonlinear dynamical systems · Joar AxåsMattia CenedeseG. Haller. Engineering, Computer Science. Nonlinear dynamics. 2022.
Nonlinear model reduction from equations and data - AIP Publishing
Other reduction approaches rooted in dynamical systems theory seek to compute low-dimensional, attracting invariant manifolds. Related methods ...
George Haller's Group for Nonlinear Dynamical Systems
Equation- and Data-Driven Nonlinear Model Reduction to Spectral Submanifolds by Prof. ... Fast Reduction of Nonlinear Finite Element Models to Spectral ...
Non-intrusive model reduction of large-scale, nonlinear dynamical ...
Peherstofer and Wilcox [12] proposed a data-driven operator inference approach based on least square fitting to establish a non-intrusive projection-based ROM ...
Model Reduction for Nonlinear Dynamical Systems with Parametric ...
Nonlinear dynamical systems are known to be sensitive to input parameters. In this thesis, we apply model order reduction to an important class of such systems.
Data-driven nonlinear model reduction to spectral submanifolds in ...
... Data-driven prediction in dynamical systems'. ... Faster timescales of the dynamics can be extracted from trajectory data by model reduction ...
Accurate error estimation for model reduction of nonlinear dynamical ...
To achieve this, we introduce a corrected reduced-order model which takes into account a data-driven closure term for improved accuracy. The closure term, ...
Nonlinear model reduction to fractional and mixed-mode spectral ...
dynamical systems and obtain data-driven reduced models on such ... 107,. 1417–1450 (2022). 27J. Axås, M. Cenedese, and G. Haller, “Fast data- ...
Nonlinear Model Reduction for Slow-Fast Stochastic Systems near ...
This construction enables fast, efficient simulation of the effective dynamics that averages out fast modes, plus estimation of crucial ...