14 citations · 30 across the 14 of their papers we have counts for
3 papers · 1 filter
Meta-State-Space Learning: An Identification Approach for Stochastic Dynamical Systems
Gerben I. Beintema, Maarten Schoukens, Roland Tóth
Available methods for identification of stochastic dynamical systems from input-output data generally impose restricting structural assumptions on either the noise structure in the…
Initialization Approach for Nonlinear State-Space Identification via the Subspace Encoder Approach
Rishi Ramkannan, Gerben I. Beintema, Roland Tóth +1
The SUBNET neural network architecture has been developed to identify nonlinear state-space models from input-output data. To achieve this, it combines the rolled-out nonlinear sta…
Computationally efficient predictive control based on ANN state-space models
Jan H. Hoekstra, Bence Cseppentő, Gerben I. Beintema +3
Artificial neural networks (ANN) have been shown to be flexible and effective function estimators for identification of nonlinear state-space models. However, if the resulting mode…