This work investigates the stability of (discrete) empirical interpolation for nonlinear model reduction and state field approximation from measurements.
This thesis proposed a model reduction technique for nonlinear dynamical systems based upon combining Proper Orthogonal Decomposition (POD) and a new method.
Discrete Empirical Interpolation Method (DEIM) ... reduced vars. DEIM Point Selection Algorithm. Demonstrated Accuracy and Efficiency. Nonlinear MOR via DEIM.
This thesis proposes a model reduction technique for nonlinear dynamical systems based upon combining Proper Orthogonal Decomposition (POD) and a new method ...
A dimension reduction method called discrete empirical interpolation is proposed and shown to dramatically reduce the computational complexity of the ...
Dec 1, 2023 · We present a model reduction approach that extends the original empirical interpolation method to enable accurate and efficient reduced basis approximation.
Nonlinear Model Reduction via Discrete Empirical Interpolation
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Nonlinear Model Reduction via Discrete Empirical Interpolation. Chaturantabut, Saifon; ;; Sorensen, Danny C. Abstract. Publication: SIAM Journal on Scientific ...
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The discrete empirical interpolation method (DEIM) is a popular technique for nonlinear model reduction, and it has two main ingredients: an interpolating basis ...
Oct 22, 2024 · For this method, the nonlinear system is replaced by a weighted sum of linear systems; these linear systems can then be reduced by using well- ...
In this paper, we introduce the neural empirical interpolation method (NEIM), a neural network-based alternative to the discrete empirical interpolation method ...