| Modeling and identification of linear parameter-varying systems R Tóth Springer, 2010 | 707 | 2010 |
| Smoke: Single-stage monocular 3d object detection via keypoint estimation Z Liu, Z Wu, R Tóth Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 376 | 2020 |
| Refined instrumental variable methods for identification of LPV Box–Jenkins models V Laurain, M Gilson, R Tóth, H Garnier Automatica 46 (6), 959-967, 2010 | 195 | 2010 |
| On the state-space realization of LPV input-output models: Practical approaches R Tóth, HS Abbas, H Werner IEEE transactions on control systems technology 20 (1), 139-153, 2011 | 155 | 2011 |
| A review on data-driven linear parameter-varying modeling approaches: A high-purity distillation column case study AA Bachnas, R Tóth, JHA Ludlage, A Mesbah Journal of Process Control 24 (4), 272-285, 2014 | 146 | 2014 |
| Discrete time LPV I/O and state space representations, differences of behavior and pitfalls of interpolation R Tóth, F Felici, PSC Heuberger, PMJ Van den Hof 2007 European Control Conference (ECC), 5418-5425, 2007 | 135 | 2007 |
| Asymptotically optimal orthonormal basis functions for LPV system identification R Tóth, PSC Heuberger, PMJ Van den Hof Automatica 45 (6), 1359-1370, 2009 | 116 | 2009 |
| Modeling and identification of linear parameter-varying systems: an orthonormal basis function approach R Tóth | 110 | 2008 |
| Discretisation of linear parameter-varying state-space representations R Tóth, PSC Heuberger, PMJ Van den Hof IET control theory & applications 4 (10), 2082-2096, 2010 | 90 | 2010 |
| Direct learning of LPV controllers from data S Formentin, D Piga, R Tóth, SM Savaresi Automatica 65, 98-110, 2016 | 84 | 2016 |
| The behavioral approach to linear parameter-varying systems R Tóth, JC Willems, PSC Heuberger, PMJ Van den Hof IEEE Transactions on Automatic Control 56 (11), 2499-2514, 2011 | 80 | 2011 |
| Model structure learning: A support vector machine approach for LPV linear-regression models R Tóth, V Laurain, WX Zheng, K Poolla 2011 50th IEEE Conference on Decision and Control and European Control …, 2011 | 70 | 2011 |
| Instrumental variable scheme for closed-loop LPV model identification R Toth, V Laurain, M Gilson, H Garnier Automatica 48 (9), 2314-2320, 2012 | 63 | 2012 |
| Compressive system identification of LTI and LTV ARX models BM Sanandaji, TL Vincent, MB Wakin, R Tóth, K Poolla 2011 50th IEEE Conference on Decision and Control and European Control …, 2011 | 63 | 2011 |
| State-space LPV model identification using kernelized machine learning SZ Rizvi, JM Velni, F Abbasi, R Tóth, N Meskin Automatica 88, 38-47, 2018 | 62 | 2018 |
| Compressive system identification in the linear time-invariant framework R Tóth, BM Sanandaji, K Poolla, TL Vincent 2011 50th IEEE Conference on Decision and Control and European Control …, 2011 | 56 | 2011 |
| Data-driven predictive control for linear parameter-varying systems C Verhoek, HS Abbas, R Tóth, S Haesaert IFAC-PapersOnLine 54 (8), 101-108, 2021 | 55 | 2021 |
| LPV system identification under noise corrupted scheduling and output signal observations D Piga, P Cox, R Tóth, V Laurain Automatica 53, 329-338, 2015 | 55 | 2015 |
| Stabilizing tube-based model predictive control: Terminal set and cost construction for LPV systems J Hanema, M Lazar, R Tóth Automatica 85, 137-144, 2017 | 53 | 2017 |
| On the discretization of linear fractional representations of LPV systems R Tóth, M Lovera, PSC Heuberger, M Corno, PMJ Van den Hof IEEE Transactions on Control Systems Technology 20 (6), 1473-1489, 2011 | 53 | 2011 |
Paul M.J. Van den HofProfessor Eindhoven University of Technology在 tue.nl 的电子邮件经过验证
