14 citations · 30 across the 14 of their papers we have counts for
4 papers · 1 filter
Deep Subspace Encoders for Nonlinear System Identification
Gerben I. Beintema, Maarten Schoukens, Roland Tóth
Using Artificial Neural Networks (ANN) for nonlinear system identification has proven to be a promising approach, but despite of all recent research efforts, many practical and the…
Continuous-time identification of dynamic state-space models by deep subspace encoding
Gerben I. Beintema, Maarten Schoukens, Roland Tóth
Continuous-time (CT) modeling has proven to provide improved sample efficiency and interpretability in learning the dynamical behavior of physical systems compared to discrete-time…
NARX Identification using Derivative-Based Regularized Neural Networks
L. H. Peeters, G. I. Beintema, M. Forgione +1
This work presents a novel regularization method for the identification of Nonlinear Autoregressive eXogenous (NARX) models. The regularization method promotes the exponential deca…
Deep-Learning-Based Identification of LPV Models for Nonlinear Systems
Chris Verhoek, Gerben I. Beintema, Sofie Haesaert +2
The Linear Parameter-Varying (LPV) framework provides a modeling and control design toolchain to address nonlinear (NL) system behavior via linear surrogate models. Despite major r…