Items where Author is "Beintema, G I"
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Number of items: 10.
2021
| Date | Author/Title | Document Type | |
|---|---|---|---|
| 2021 | Iacob, L C and Beintema, G I and Schoukens, M and Tóth, Roland Deep Identification of Nonlinear Systems in Koopman Form |  | Book Section |
| 2021 | Rödönyi, Gábor and Beintema, G I and Tóth, Roland and Schoukens, M and Pup, Dániel and Kisari, Ádám and Vigh, Zsombor and Kőrös, Péter and Soumelidis, Alexandros and Bokor, József Identification of the nonlinear steering dynamics of an autonomous vehicle | Article | |
| 2021 | Beintema, G I and Tóth, Roland and Schoukens, M Non-linear State-space Model Identification from Video Data using Deep Encoders | Article |
2022
| Date | Author/Title | Document Type | |
|---|---|---|---|
| 2022 | Verhoek, C and Beintema, G I and Haesaert, S and Schoukens, M and Tóth, Roland Deep-Learning-Based Identification of LPV Models for Nonlinear Systems | Book Section |
2023
| Date | Author/Title | Document Type | |
|---|---|---|---|
| 2023 | Hoekstra, J H and Cseppentő, Bence and Beintema, G I and Schouken, M and Kollár, Zsolt and Tóth, Roland Computationally efficient predictive control based on ANN state-space models | | Book Section |
| 2023 | Beintema, G I and Schoukens, M and Tóth, Roland Continuous-time identification of dynamic state-space models by deep subspace encoding | | Conference or Workshop Item |
| 2023 | Beintema, G I and Schoukens, M and Tóth, Roland Deep subspace encoders for nonlinear system identification | | Article |
| 2023 | Ramkannan, R and Beintema, G I and Tóth, Roland and Schoukens, M Initialization Approach for Nonlinear State-Space Identification via the Subspace Encoder Approach | | Article |
2024
| Date | Author/Title | Document Type | |
|---|---|---|---|
| 2024 | Retzler, András and Tóth, Roland and Schoukens, M and Beintema, G I and Weigand, J and Noël, J-P and Kollár, Zsolt and Swevers, J Learning-based augmentation of physics-based models: an industrial robot use case | | Article |
| 2024 | Beintema, G I and Schoukens, M and Tóth, Roland Meta-state–space learning: An identification approach for stochastic dynamical systems | | Article |
