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Pepijn B. Cox
Pepijn B. Cox
Research Scientist for the TNO Radar Department
Verified email at tno.nl - Homepage
Title
Cited by
Cited by
Year
LPV system identification under noise corrupted scheduling and output signal observations
D Piga, P Cox, R Tóth, V Laurain
Automatica 53, 329-338, 2015
522015
Linear parameter-varying subspace identification: A unified framework
PB Cox, R Tóth
Automatica 123, 109296, 2021
382021
Towards efficient maximum likelihood estimation of LPV-SS models
PB Cox, R Tóth, M Petreczky
Automatica 97, 392-403, 2018
302018
Affine parameter-dependent lyapunov functions for LPV systems with affine dependence
PB Cox, S Weiland, R Tóth
IEEE Transactions on Automatic Control, 2019
282019
Towards efficient identification of linear parameter-varying state-space models
PB Cox
Eindhoven University of Technology, 2018
282018
LPVcore: MATLAB toolbox for LPV modelling, identification and control
P den Boef, PB Cox, R Tóth
IFAC-PapersOnLine 54 (7), 385-390, 2021
252021
Predictionerror identification of LPV systems: a nonparametric gaussian regression approach
R Darwish, M. A. H. and Cox, P. B. and Proimadis, I. and Pillonetto, G. and Tóth
Automatica 97, 92-103, 2018
242018
Bayesian identification of LPV Box-Jenkins models
M Darwish, P Cox, G Pillonetto, R Tóth
2015 54th IEEE Conference on Decision and Control (CDC), 66-71, 2015
132015
Estimation of LPV-SS models with static dependency using correlation analysis
PB Cox, R Tóth, M Petreczky
Proceedings of the 1st IFAC Workshop on Linear Parameter Varying Systems 48 …, 2015
112015
LPV state-space identification via IO methods and efficient model order reduction in comparison with subspace methods
E Schulz, PB Cox, R Toth, H Werner
2017 IEEE 56th Annual Conference on Decision and Control (CDC), 3575-3581, 2017
82017
CVA identification of nonlinear systems with LPV state-space models of affine dependence
WE Larimore, PB Cox, R Tóth
2015 American Control Conference (ACC), 831-837, 2015
82015
Alternative form of predictor based identification of LPV-SS models with innovation noise
P Cox, R Tóth
Decision and Control (CDC), 2016 IEEE 55th Conference on, 1223-1228, 2016
62016
LPV state-space model identification in the Bayesian setting: A 3-step procedure
PB Cox, R Tóth
2016 American Control Conference (ACC), 4604-4610, 2016
52016
Analysing Multibeam, Cooperative, Ground Based Radar in a Bistatic Configuration
PB Cox, WL van Rossum
2020 IEEE International Radar Conference (RADAR), 912-917, 2020
22020
System for deterring birds
SFB Henskes, PRC Tammes, T Sprang, PB Cox
US Patent 10,251,386, 2019
22019
Description of the data generating system utilized in “prediction-error identification of LPV systems: a nonparametric gaussian regression approach”
MAH Darwish, PB Cox, I Proimadis, G Pillonetto, R Toth
Eindhoven University of Technology, Tech. Rep. TUE-CS-2017-001, 2017
22017
Efficient Processing of Irregular PRF Waveforms: Clutter Suppression and Approximate 2D Matched Filtering
K Klein, M Coutino, R Struiksma, P Cox, L Anitori
2023 IEEE Radar Conference (RadarConf23), 1-6, 2023
12023
Kernel Design Meets Clutter Cancellation for Irregular Waveforms
PB Cox, MA Coutiño, WL van Rossum
2023 IEEE Radar Conference (RadarConf23), 1-6, 2023
12023
On the connection between different noise structures for LPV-SS models
PB Cox, R Tóth
arXiv preprint arXiv:1610.09173, 2016
12016
Cramér-Rao Lower Bound and Estimation Algorithms For Scene-based Bistatic Radar Waveform Estimation
M Coutino, AM Sardarabadi, P Cox, W Van Rossum, L Anitori
2023 IEEE Radar Conference (RadarConf23), 1-6, 2023
2023
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