Identification of nonlinear systems using polynomial nonlinear state space models J Paduart, L Lauwers, J Swevers, K Smolders, J Schoukens, R Pintelon Automatica 46 (4), 647-656, 2010 | 349 | 2010 |
Identification of a Wiener–Hammerstein system using the polynomial nonlinear state space approach J Paduart, L Lauwers, R Pintelon, J Schoukens Control Engineering Practice 20 (11), 1133-1139, 2012 | 70 | 2012 |
Identification of Wiener–Hammerstein models: Two algorithms based on the best split of a linear model applied to the SYSID'09 benchmark problem J Sjöberg, L Lauwers, J Schoukens Control Engineering Practice 20 (11), 1119-1125, 2012 | 47 | 2012 |
Linearizing oscillometric blood-pressure measurements:(Non) sense? W Van Moer, L Lauwers, D Schoors, K Barbe IEEE Transactions on Instrumentation and Measurement 60 (4), 1267-1275, 2011 | 37 | 2011 |
Estimating the parameters of a Rice distribution: A Bayesian approach L Lauwers, K Barbé, W Van Moer, R Pintelon 2009 IEEE Instrumentation and Measurement Technology Conference, 114-117, 2009 | 37 | 2009 |
Identification of a wiener-hammerstein system using the polynomial nonlinear state space approach J Paduart, L Lauwers, R Pintelon, J Schoukens IFAC Proceedings Volumes 42 (10), 1080-1085, 2009 | 29 | 2009 |
A nonlinear block structure identification procedure using frequency response function measurements L Lauwers, J Schoukens, R Pintelon, M Enqvist IEEE Transactions on Instrumentation and Measurement 57 (10), 2257-2264, 2008 | 29 | 2008 |
Some practical applications of the best linear approximation in nonlinear block-oriented modelling L Lauwers Vrije Universiteit Brussel, 2011 | 19 | 2011 |
Fractional models for modeling complex linear systems under poor frequency resolution measurements K Barbé, OJO Rodriguez, W Van Moer, L Lauwers Digital Signal Processing 23 (4), 1084-1093, 2013 | 17 | 2013 |
Functional magnetic resonance imaging: An improved short record signal model K Barbe, W Van Moer, L Lauwers IEEE Transactions on Instrumentation and Measurement 60 (5), 1724-1731, 2010 | 17 | 2010 |
Modelling of Wiener-Hammerstein systems via the best linear approximation L Lauwers, R Pintelon, J Schoukens IFAC Proceedings Volumes 42 (10), 1098-1103, 2009 | 15 | 2009 |
Analyzing Rice distributed functional magnetic resonance imaging data: a Bayesian approach L Lauwers, K Barbé, W Van Moer, R Pintelon Measurement Science and Technology 21 (11), 115804, 2010 | 14 | 2010 |
Oscillometric blood pressure measurements: A signal analysis K Barbé, W Van Moer, L Lauwers Journal of Physics: Conference Series 238 (1), 012052, 2010 | 14 | 2010 |
Nonlinear structure analysis using the best linear approximation L Lauwers, J Schoukens, M Enqvist, R Pintelon UAP-PAI V/22 workshop on Dynamical Systems and Control: computation …, 2006 | 14 | 2006 |
A guaranteed blind and automatic probability density estimation of raw measurements K Barbé, LG Fuentes, L Barford, L Lauwers IEEE Transactions on Instrumentation and Measurement 63 (9), 2120-2128, 2014 | 12 | 2014 |
A simple nonparametric preprocessing technique to correct for nonstationary effects in measured data K Barbé, W Van Moer, L Lauwers, N Björsell IEEE Transactions on Instrumentation and Measurement 61 (8), 2085-2094, 2012 | 7 | 2012 |
Some applications of the best linear approximation in nonlinear block-oriented modelling L Lauwers Ph. D. dissertation, Dept. Fundam. Elect. Instrum., Vrije Univ., Brussel …, 2011 | 7 | 2011 |
Initial Estimates for Wiener-Hammerstein Models using the Best Linear Approximation L Lauwers, J Schoukens, R Pintelon 2008 IEEE Instrumentation and Measurement Technology Conference, 928-932, 2008 | 7 | 2008 |
Improved variance estimates of FRF measurements in the presence of nonlinear distortions via overlap K Barbé, R Pintelon, J Schoukens, L Lauwers IEEE Transactions on Instrumentation and Measurement 60 (1), 300-309, 2010 | 6 | 2010 |
A qualitative study of probability density visualization techniques in measurements L Gonzales-Fuentes, K Barbé, L Barford, L Lauwers, L Philips Measurement 65, 94-111, 2015 | 5 | 2015 |