- Data|driven model reduction for weakly nonlinear systems🔍
- Fast data|driven model reduction for nonlinear dynamical systems🔍
- Data|driven modeling and prediction of non|linearizable dynamics ...🔍
- A data|driven approach to nonlinear model reduction🔍
- Model Reduction of Weakly Nonlinear Systems🔍
- Learning Nonlinear Reduced Models from Data with Operator ...🔍
- Nonlinear Reduced|Order Modeling from Data by Prof. George Haller.🔍
- 7 Data|driven methods for reduced|order modeling🔍
Data|driven model reduction for weakly nonlinear systems
Data-driven model reduction for weakly nonlinear systems: A summary
Data-driven model reduction for weakly nonlinear systems: A summary☆. Author links open overlay panel A.C. Antoulas 1 2 , I.V. Gosea 3. Show more.
Data-driven model reduction for weakly nonlinear systems: A ...
Request PDF | Data-driven model reduction for weakly nonlinear systems: A summary | Model reduction seeks to replace complex dynamical systems with simpler ...
Fast data-driven model reduction for nonlinear dynamical systems
Abstract We present a fast method for nonlinear data- driven model reduction of dynamical systems onto their.
Data-driven modeling and prediction of non-linearizable dynamics ...
Low-dimensional reduced models of high-dimensional nonlinear dynamical systems are critically needed in various branches of applied science and ...
First, we transform the. Euler equations in conservative variables to the specific volume state representation, yielding low-dimensional Transform & Learn ...
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).
Model Reduction of Weakly Nonlinear Systems - SpringerLink
Model Reduction of Weakly Nonlinear Systems ... In general, model reduction techniques fall into two categories — moment —matching and Krylov techniques and ...
Learning Nonlinear Reduced Models from Data with Operator ...
This review discusses Operator Inference, a nonintrusive reduced model- ing approach that incorporates physical governing equations by defining ...
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 ...
7 Data-driven methods for reduced-order modeling - De Gruyter
... dynamical systems, which are amenable to simple analysis techniques. The ... nonlinear manifold by making the spatiotemporal dynamics weakly nonlinear.
Data-driven model reduction for weakly nonlinear systems: A ...
Journal name. IFAC-PapersOnLine. Page range. 3-4. Date. Sun, 02/01/2015 - 12:00. Scopus ID. SCOPUS_ID:84954101459. Volume. 28. Issue Identifier.
Projection frameworks for model reduction of weakly nonlinear ...
Projection frameworks for model reduction of weakly nonlinear systems. Joel R. Phillips. Cadence Berkeley Laboratories, San Jose, CA 95134. Abstract. In this ...
Data-driven modeling and complexity reduction for nonlinear ...
The research reported in this thesis is part of the research program of the Dutch Institute of Systems and Control (DISC). The author has ...
NORM: compact model order reduction of weakly nonlinear systems ...
This paper presents a compact Nonlinear model Order Reduction Method (NORM) that is applicable for time-invariant and time-varying weakly nonlinear systems.
Data-Driven Dimension Reduction of Linear and Nonlinear Systems
I.V. Gosea and A.C. Antoulas "Data-driven model reduction for weakly nonlinear systems: A summary" IFAC-PapersOnLine , v.48 , 2015. IV Gosea ...
Data-driven nonlinear model reduction to spectral submanifolds in ...
While data-driven model reduction techniques are well-established for linearizable mechanical systems, general approaches to reducing ...
Non-intrusive Data-driven Model Reduction for Differential Algebraic ...
The approach considers the particular case of nonlinear partial differential equations (PDEs) that form systems of partial differential-.
Analytical Phase Reduction for Weakly Nonlinear Oscillators - arXiv
Nonlinear Sciences > Adaptation and Self-Organizing Systems · Title:Analytical Phase Reduction for Weakly Nonlinear Oscillators · Bibliographic ...
Weakly Nonlinear Surface Wave Prediction Using a Data-Driven ...
[21,22] applied the ANN model to predict weakly spread waves in both synthetic and field data, comparing their results with physics-based models. It is ...
Nonlinear Model Reduction for Control Workshop and Conference ...
invariant systems, an important sub-class of weakly-nonlinear dynamical systems. ... data driven modeling of dynamical systems in diverse ...