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2020 – today
- 2023
[j164]Paolo Carbone
, Alessio De Angelis, Johan Schoukens, Antonio Moschitta, Francesco Santoni:
Low-Complexity Electrochemical-Impedance Spectroscopy for Battery Monitoring. IEEE Trans. Instrum. Meas. 72: 1-9 (2023)- [c51]Paolo Carbone, Alessio De Angelis, Johan Schoukens, Antonio Moschitta, Francesco Santoni:
Asymptotic Properties of a One-bit Estimator of Parametric Signals. I2MTC 2023: 1-6 - 2022
- [j163]Karthik Raghavan Ramaswamy, Péter Zoltán Csurcsia, Johan Schoukens, Paul M. J. Van den Hof:
A frequency domain approach for local module identification in dynamic networks. Autom. 142: 110370 (2022) - [j162]Paolo Carbone, Johan Schoukens, Alessio De Angelis, Antonio Moschitta, Francesco Santoni:
One-Bit Constrained Measurements of Parametric Signals. IEEE Trans. Instrum. Meas. 71: 1-13 (2022) - [i38]Kiana Karami, David T. Westwick, Johan Schoukens:
Applying Polynomial Decoupling Methods to the Polynomial NARX Model. CoRR abs/2202.12423 (2022) - [i37]Jan Decuyper, Koen Tiels, Siep Weiland, Mark C. Runacres, Johan Schoukens:
Decoupling multivariate functions using a nonparametric filtered tensor decomposition. CoRR abs/2205.11153 (2022) - 2021
- [j161]Paolo Carbone, Johan Schoukens, Alessio De Angelis, Francesco Santoni, Antonella Comuniello, Antonio Moschitta:
One-Bit Sine-Fit. IEEE Trans. Instrum. Meas. 70: 1-12 (2021) - [i36]Jan Decuyper, Koen Tiels, Siep Weiland, Johan Schoukens:
Decoupling multivariate functions using a non-parametric Filtered CPD approach. CoRR abs/2105.08518 (2021) - [i35]Jan Decuyper, David T. Westwick, Kiana Karami, Johan Schoukens:
Decoupling P-NARX models using filtered CPD. CoRR abs/2105.08530 (2021) - [i34]Jan Decuyper, Koen Tiels, Johan Schoukens:
PNLSS Toolbox 1.0. CoRR abs/2105.08534 (2021) - [i33]Karthik Raghavan Ramaswamy, Péter Zoltán Csurcsia, Johan Schoukens, Paul M. J. Van den Hof:
A frequency domain approach for local module identification in dynamic networks. CoRR abs/2105.10901 (2021) - 2020
- [j160]Maarten Schoukens, Rik Pintelon, Tadeusz P. Dobrowiecki, Johan Schoukens:
Extending the Best Linear Approximation Framework to the Process Noise Case. IEEE Trans. Autom. Control. 65(4): 1514-1524 (2020) - [j159]Paolo Carbone, Johan Schoukens, Antonio Moschitta:
Quick Estimation of Periodic Signal Parameters From 1-Bit Measurements. IEEE Trans. Instrum. Meas. 69(2): 339-353 (2020) - [j158]Dieter Verbeke, Johan Schoukens:
Frequency Response Measurements With Local Parametric Modeling. IEEE Trans. Instrum. Meas. 69(6): 3249-3261 (2020) - [j157]Paolo Carbone, Johan Schoukens, Alessio De Angelis, Antonio Moschitta:
Frequency and Amplitude Domain DAC-ADC Co-Testing Using Ternary Signals. IEEE Trans. Instrum. Meas. 69(7): 4042-4055 (2020) - [j156]Paolo Carbone, Johan Schoukens, Alessio De Angelis, Antonio Moschitta:
A 1.5-bit DFT Analyzer. IEEE Trans. Instrum. Meas. 69(10): 8590-8599 (2020) - [i32]Jan Decuyper, Koen Tiels, Mark C. Runacres, Johan Schoukens:
Retrieving highly structured models starting from black-box nonlinear state-space models using polynomial decoupling. CoRR abs/2001.02861 (2020) - [i31]Jan Decuyper, Tim De Troyer, Koen Tiels, Johan Schoukens, Mark C. Runacres:
A nonlinear model of vortex-induced forces on an oscillating cylinder in a fluid flow. CoRR abs/2006.05932 (2020)
2010 – 2019
- 2019
- [j155]Jeremy Stoddard, Georgios Birpoutsoukis, Johan Schoukens, James S. Welsh:
Gaussian process regression for the estimation of generalized frequency response functions. Autom. 106: 161-167 (2019) - [j154]Ralf Stroop, Makoto Nakamura, Johan Schoukens, David Oliva Uribe:
Tactile sensor-based real-time clustering for tissue differentiation. Int. J. Comput. Assist. Radiol. Surg. 14(1): 129-137 (2019) - [j153]Jan Decuyper, Philippe Dreesen, Johan Schoukens, Mark Runacres, Koen Tiels:
Decoupling Multivariate Polynomials for Nonlinear State-Space Models. IEEE Control. Syst. Lett. 3(3): 745-750 (2019) - [c50]Kiana Karami, David T. Westwick, Johan Schoukens:
Identification of Decoupled Polynomial NARX Model Using Simulation Error Minimization. ACC 2019: 4362-4367 - [i30]Johan Schoukens, Lennart Ljung:
Nonlinear System Identification: A User-Oriented Roadmap. CoRR abs/1902.00683 (2019) - 2018
- [j152]Jean-Philippe Noël, Johan Schoukens:
Grey-box state-space identification of nonlinear mechanical vibrations. Int. J. Control 91(5): 1118-1139 (2018) - [j151]Gabriel Hollander, Philippe Dreesen, Mariya Ishteva, Johan Schoukens:
Approximate decoupling of multivariate polynomials using weighted tensor decomposition. Numer. Linear Algebra Appl. 25(2) (2018) - [j150]Alessio De Angelis, Johan Schoukens, Keith R. Godfrey, Paolo Carbone:
Best Linear Approximation of Wiener Systems Using Multilevel Signals: Theory and Experiments. IEEE Trans. Instrum. Meas. 67(5): 1246-1253 (2018) - [j149]Paolo Carbone, Johan Schoukens, Antonio Moschitta:
Joint Measurement of Signal Parameters and ADC Transition Levels. IEEE Trans. Instrum. Meas. 67(12): 2752-2760 (2018) - [c49]Alessio De Angelis, Paolo Carbone, Johan Schoukens:
Generating low-distortion ternary signals using an imperfect DAC and ADC chain. I2MTC 2018: 1-6 - [i29]Anna Marconato, Maarten Schoukens, Koen Tiels, Widanalage Dhammika Widanage, Amjad Abu-Rmileh, Johan Schoukens:
Comparison of several data-driven nonlinear system identification methods on a simplified glucoregulatory system example. CoRR abs/1804.07035 (2018) - [i28]Maarten Schoukens, Rik Pintelon, Tadeusz P. Dobrowiecki, Johan Schoukens:
Extending the Best Linear Approximation Framework to the Process Noise Case. CoRR abs/1804.07510 (2018) - [i27]Alessio De Angelis, Johan Schoukens, Keith R. Godfrey, Paolo Carbone:
Practical Issues in the Synthesis of Ternary Sequences. CoRR abs/1804.07701 (2018) - [i26]Jan Decuyper, Tim De Troyer, Mark Runacres, Koen Tiels, Johan Schoukens:
Nonlinear state-space modelling of the kinematics of an oscillating circular cylinder in a fluid flow. CoRR abs/1804.08383 (2018) - [i25]Anna Marconato, Jonas Sjöberg, Johan A. K. Suykens, Johan Schoukens:
Improved Initialization for Nonlinear State-Space Modeling. CoRR abs/1804.08654 (2018) - [i24]Johan Schoukens, Mark Vaes, Rik Pintelon:
Linear System Identification in a Nonlinear Setting - Nonparametric analysis of the nonlinear distortions and their impact on the best linear approximation. CoRR abs/1804.09587 (2018) - [i23]Johan Schoukens, Rik Pintelon, Yves Rolain, Maarten Schoukens, Koen Tiels, Laurent Vanbeylen, Anne Van Mulders, Gerd Vandersteen:
Structure Discrimination in Block-Oriented Models Using Linear Approximations: A Theoretic Framework. CoRR abs/1804.09648 (2018) - [i22]Erliang Zhang, Maarten Schoukens, Johan Schoukens:
Structure detection of Wiener-Hammerstein systems with process noise. CoRR abs/1804.10022 (2018) - [i21]Georgios Birpoutsoukis, Péter Zoltán Csurcsia, Johan Schoukens:
Efficient Multidimensional Regularization for Volterra Series Estimation. CoRR abs/1804.10026 (2018) - [i20]Georgios Birpoutsoukis, Anna Marconato, John Lataire, Johan Schoukens:
Regularized Nonparametric Volterra Kernel Estimation. CoRR abs/1804.10435 (2018) - [i19]Jean-Philippe Noël, Johan Schoukens:
Grey-box state-space identification of nonlinear mechanical vibrations. CoRR abs/1804.10758 (2018) - [i18]Alireza Fakhrizadeh Esfahani, Johan Schoukens, Laurent Vanbeylen:
Using the Best Linear Approximation With Varying Excitation Signals for Nonlinear System Characterization. CoRR abs/1805.04575 (2018) - [i17]Rishi Relan, Johan Schoukens:
Recursive Discrete-Time Models for Continuous-Time Systems Under Band-Limited Assumptions. CoRR abs/1805.05040 (2018) - [i16]Rishi Relan, Koen Tiels, Jean-Marc Timmermans, Johan Schoukens:
A Local Polynomial Approach to Nonparametric Estimation of the Best Linear Approximation of Lithium-Ion Battery From Multiple Datasets. CoRR abs/1805.06237 (2018) - [i15]Rishi Relan, Koen Tiels, Anna Marconato, Philippe Dreesen, Johan Schoukens:
Data driven discrete-time parsimonious identification of a nonlinear state-space model for a weakly nonlinear system with short data record. CoRR abs/1805.06252 (2018) - [i14]Rishi Relan, Yousef Firouz, Jean-Marc Timmermans, Johan Schoukens:
Data-Driven Nonlinear Identification of Li-Ion Battery Based on a Frequency Domain Nonparametric Analysis. CoRR abs/1805.06702 (2018) - 2017
- [j148]Georgios Birpoutsoukis, Anna Marconato, John Lataire, Johan Schoukens:
Regularized nonparametric Volterra kernel estimation. Autom. 82: 324-327 (2017) - [j147]Rishi Relan, Koen Tiels, Jean-Marc Timmermans, Johan Schoukens:
A Local Polynomial Approach to Nonparametric Estimation of the Best Linear Approximation of Lithium-Ion Battery From Multiple Datasets. IEEE Control. Syst. Lett. 1(1): 182-187 (2017) - [j146]Rishi Relan, Yousef Firouz, Jean-Marc Timmermans, Johan Schoukens:
Data-Driven Nonlinear Identification of Li-Ion Battery Based on a Frequency Domain Nonparametric Analysis. IEEE Trans. Control. Syst. Technol. 25(5): 1825-1832 (2017) - [j145]Alessio De Angelis, Johan Schoukens, Keith R. Godfrey, Paolo Carbone:
Practical Issues in the Synthesis of Ternary Sequences. IEEE Trans. Instrum. Meas. 66(2): 212-222 (2017) - [j144]Paolo Carbone, Johan Schoukens, Antonio Moschitta:
Dynamic Signal Measurements Based on Quantized Data. IEEE Trans. Instrum. Meas. 66(2): 223-233 (2017) - [j143]Hannes Maes, Miroslav Zivanovic, Johan Schoukens, Gerd Vandersteen:
Estimating Respiratory Impedance at Breathing Frequencies Using Regularized Least Squares on Forced Oscillation Technique Measurements. IEEE Trans. Instrum. Meas. 66(3): 479-491 (2017) - [j142]Erliang Zhang, Maarten Schoukens, Johan Schoukens:
Structure Detection of Wiener-Hammerstein Systems With Process Noise. IEEE Trans. Instrum. Meas. 66(3): 569-576 (2017) - [c48]Philippe Dreesen, Koen Tiels, Mariya Ishteva, Johan Schoukens:
Nonlinear system identification: Finding structure in nonlinear black-box models. CAMSAP 2017: 1-4 - [c47]Alessio De Angelis, Johan Schoukens, Keith R. Godfrey, Paolo Carbone:
Measuring the best linear approximation of Wiener systems using multilevel sequences. I2MTC 2017: 1-5 - [c46]Philippe Dreesen, David T. Westwick, Johan Schoukens, Mariya Ishteva:
Modeling Parallel Wiener-Hammerstein Systems Using Tensor Decomposition of Volterra Kernels. LVA/ICA 2017: 16-25 - [c45]Gabriel Hollander, Philippe Dreesen, Mariya Ishteva, Johan Schoukens:
An Initialization Method for Nonlinear Model Reduction Using the CP Decomposition. LVA/ICA 2017: 111-120 - [i13]Alexander De Cock, Michel Gevers, Johan Schoukens:
D-Optimal Input Design for Nonlinear FIR-type Systems: A Dispersion-based Approach. CoRR abs/1703.08401 (2017) - [i12]Alireza Fakhrizadeh Esfahani, Philippe Dreesen, Koen Tiels, Jean-Philippe Noël, Johan Schoukens:
Parameter reduction in nonlinear state-space identification of hysteresis. CoRR abs/1705.00178 (2017) - [i11]Alessio De Angelis, Johan Schoukens, Keith R. Godfrey, Paolo Carbone:
Best Linear Approximation of Wiener Systems Using Multilevel Signals: Theory and Experiments. CoRR abs/1710.07067 (2017) - 2016
- [j141]Per Hägg, Johan Schoukens, Michel Gevers, Håkan Hjalmarsson:
The transient impulse response modeling method for non-parametric system identification. Autom. 68: 314-328 (2016) - [j140]Kaushik Mahata, Johan Schoukens, Alexander De Cock:
Information matrix and D-optimal design with Gaussian inputs for Wiener model identification. Autom. 69: 65-77 (2016) - [j139]Alexander De Cock, Michel Gevers, Johan Schoukens:
D-optimal input design for nonlinear FIR-type systems: A dispersion-based approach. Autom. 73: 88-100 (2016) - [j138]Rishi Relan, Johan Schoukens:
Recursive Discrete-Time Models for Continuous-Time Systems Under Band-Limited Assumptions. IEEE Trans. Instrum. Meas. 65(3): 713-723 (2016) - [j137]Alireza Fakhrizadeh Esfahani, Johan Schoukens, Laurent Vanbeylen:
Using the Best Linear Approximation With Varying Excitation Signals for Nonlinear System Characterization. IEEE Trans. Instrum. Meas. 65(5): 1271-1280 (2016) - [j136]Paolo Carbone, Johan Schoukens, István Kollár, Antonio Moschitta:
Measuring the Noise Cumulative Distribution Function Using Quantized Data. IEEE Trans. Instrum. Meas. 65(7): 1540-1546 (2016) - [c44]Anna Marconato, Maarten Schoukens, Johan Schoukens:
Filter interpretation of regularized impulse response modeling. ECC 2016: 1655-1660 - [c43]Alessio De Angelis, Johan Schoukens, Keith R. Godfrey, Paolo Carbone:
Practical synthesis of ternary sequences for system identification. I2MTC 2016: 1-6 - [i10]Gabriel Hollander, Philippe Dreesen, Mariya Ishteva, Johan Schoukens:
Weighted tensor decomposition for approximate decoupling of multivariate polynomials. CoRR abs/1601.07800 (2016) - [i9]Philippe Dreesen, David T. Westwick, Johan Schoukens, Mariya Ishteva:
Modeling Parallel Wiener-Hammerstein Systems Using Tensor Decomposition of Volterra Kernels. CoRR abs/1609.08063 (2016) - [i8]Anna Marconato, Maarten Schoukens, Johan Schoukens:
Filter-based regularisation for impulse response modelling. CoRR abs/1610.07353 (2016) - [i7]Jean-Philippe Noël, Alireza Fakhrizadeh Esfahani, Gaetan Kerschen, Johan Schoukens:
A nonlinear state-space approach to hysteresis identification. CoRR abs/1610.09138 (2016) - [i6]Jean-Philippe Noël, Johan Schoukens, Gaetan Kerschen:
Grey-box nonlinear state-space modelling for mechanical vibrations identification. CoRR abs/1610.09145 (2016) - [i5]Koen Tiels, Johan Schoukens:
Wiener system identification with generalized orthonormal basis functions. CoRR abs/1612.04558 (2016) - [i4]Koen Tiels, Maarten Schoukens, Johan Schoukens:
Initial estimates for Wiener-Hammerstein models using phase-coupled multisines. CoRR abs/1612.04568 (2016) - 2015
- [j135]Sándor Kolumbán, István Vajk, Johan Schoukens:
Perturbed datasets methods for hypothesis testing and structure of corresponding confidence sets. Autom. 51: 326-331 (2015) - [j134]Johan Schoukens, Rik Pintelon, Yves Rolain, Maarten Schoukens, Koen Tiels, Laurent Vanbeylen, Anne Van Mulders, Gerd Vandersteen:
Structure discrimination in block-oriented models using linear approximations: A theoretic framework. Autom. 53: 225-234 (2015) - [j133]Koen Tiels, Maarten Schoukens, Johan Schoukens:
Initial estimates for Wiener-Hammerstein models using phase-coupled multisines. Autom. 60: 201-209 (2015) - [j132]Philippe Dreesen, Mariya Ishteva, Johan Schoukens:
Decoupling Multivariate Polynomials Using First-Order Information and Tensor Decompositions. SIAM J. Matrix Anal. Appl. 36(2): 864-879 (2015) - [j131]Peter Zoltan Csurcsia, Johan Schoukens, István Kollár, John Lataire:
Nonparametric Time-Domain Identification of Linear Slowly Time-Variant Systems Using B-Splines. IEEE Trans. Instrum. Meas. 64(1): 252-262 (2015) - [j130]Antonio Moschitta, Johan Schoukens, Paolo Carbone:
Information and Statistical Efficiency When Quantizing Noisy DC Values. IEEE Trans. Instrum. Meas. 64(2): 308-317 (2015) - [j129]Antonio Moschitta, Johan Schoukens, Paolo Carbone:
Parametric System Identification Using Quantized Data. IEEE Trans. Instrum. Meas. 64(8): 2312-2322 (2015) - [j128]Paolo Carbone, Johan Schoukens, István Kollár, Antonio Moschitta:
Accurate Sine-Wave Amplitude Measurements Using Nonlinearly Quantized Data. IEEE Trans. Instrum. Meas. 64(12): 3201-3208 (2015) - [c42]Ricardo Castro-Garcia, Koen Tiels, Johan Schoukens, Johan A. K. Suykens:
Incorporating Best Linear Approximation within LS-SVM-based Hammerstein System Identification. CDC 2015: 7392-7397 - [c41]Peter Zoltan Csurcsia, Johan Schoukens:
Nonparametric estimation of a time-variant system: An experimental study of B-splines and the regularization based smoothing. I2MTC 2015: 216-221 - [c40]Georgios Birpoutsoukis, Johan Schoukens:
Nonparametric volterra kernel estimation using regularization. I2MTC 2015: 222-227 - [c39]Rishi Relan, Johan Schoukens:
Output error bounds for discrete-time models with forced delay under band-limited assumptions: An experimental study. I2MTC 2015: 228-233 - [c38]Alireza Fakhrizadeh Esfahani, Johan Schoukens, Laurent Vanbeylen:
Design of excitations for structure discrimination of nonlinear systems, using the best linear approximation. I2MTC 2015: 234-239 - [c37]Tadeusz P. Dobrowiecki, Johan Schoukens:
Reducing the measurement time of the Best Linear Approximation of a nonlinear system using improved averaging methods. I2MTC 2015: 623-628 - [c36]Anna Marconato, Johan Schoukens:
Impact of regularization in FIR estimation for short and long data records. I2MTC 2015: 789-793 - [c35]Johan Schoukens, Sándor Kolumbán:
Study of the minimum experiment length to identify linear dynamic systems: A variance based approach. I2MTC 2015: 963-968 - [c34]Philippe Dreesen, Maarten Schoukens, Koen Tiels, Johan Schoukens:
Decoupling static nonlinearities in a parallel Wiener-Hammerstein system: A first-order approach. I2MTC 2015: 987-992 - [c33]Philippe Dreesen, Thomas Goossens, Mariya Ishteva, Lieven De Lathauwer, Johan Schoukens:
Block-Decoupling Multivariate Polynomials Using the Tensor Block-Term Decomposition. LVA/ICA 2015: 14-21 - [r1]Johan Schoukens:
Frequency Domain System Identification. Encyclopedia of Systems and Control 2015 - [i3]Kaushik Mahata, Johan Schoukens:
Gaussian information matrix for Wiener model identification. CoRR abs/1510.03013 (2015) - 2014
- [j127]Koen Tiels, Johan Schoukens:
Wiener system identification with generalized orthonormal basis functions. Autom. 50(12): 3147-3154 (2014) - [j126]Clara M. Ionescu, Gerd Vandersteen, Johan Schoukens, Kristine Desager, Robin De Keyser:
Measuring Nonlinear Effects in Respiratory Mechanics: A Proof of Concept for Prototype Device and Method. IEEE Trans. Instrum. Meas. 63(1): 124-134 (2014) - [j125]Mikaya L. D. Lumori, Egon Geerardyn, Johan Schoukens, John Lataire:
Smoothing the LPM Estimate of the Frequency Response Function Via an Impulse Response Truncation Technique. IEEE Trans. Instrum. Meas. 63(1): 214-220 (2014) - [j124]Paolo Carbone, Johan Schoukens:
A Rigorous Analysis of Least Squares Sine Fitting Using Quantized Data: The Random Phase Case. IEEE Trans. Instrum. Meas. 63(3): 512-530 (2014) - [j123]Anna Marconato, Jonas Sjöberg, Johan A. K. Suykens, Johan Schoukens:
Improved Initialization for Nonlinear State-Space Modeling. IEEE Trans. Instrum. Meas. 63(4): 972-980 (2014) - [c32]Johan Schoukens, Anna Marconato, Rik Pintelon, Yves Rolain, Maarten Schoukens, Koen Tiels, Laurent Vanbeylen, Gerd Vandersteen, Anne Van Mulders:
System identification in a real world. AMC 2014: 1-9 - [c31]Ricardo Castro-Garcia, Siamak Mehrkanoon, Anna Marconato, Johan Schoukens, Johan A. K. Suykens:
SVD truncation schemes for fixed-size kernel models. IJCNN 2014: 3922-3929 - [i2]Philippe Dreesen, Mariya Ishteva, Johan Schoukens:
Decoupling Multivariate Polynomials Using First-Order Information. CoRR abs/1410.4060 (2014) - [i1]Sándor Kolumbán, István Vajk, Johan Schoukens:
Perturbed Datasets Methods for Hypothesis Testing and Structure of Corresponding Confidence Sets. CoRR abs/1412.2352 (2014) - 2013
- [j122]Torsten Söderström, Liuping Wang, Rik Pintelon, Johan Schoukens:
Can errors-in-variables systems be identified from closed-loop experiments? Autom. 49(2): 681-684 (2013) - [j121]Anne Van Mulders, Johan Schoukens, Laurent Vanbeylen:
Identification of systems with localised nonlinearity: From state-space to block-structured models. Autom. 49(5): 1392-1396 (2013) - [j120]Erliang Zhang, Rik Pintelon, Johan Schoukens:
Errors-in-variables identification of dynamic systems excited by arbitrary non-white input. Autom. 49(10): 3032-3041 (2013) - [j119]Hin Kwan Wong, Johan Schoukens, Keith R. Godfrey:
Design of Multilevel Signals for Identifying the Best Linear Approximation of Nonlinear Systems. IEEE Trans. Instrum. Meas. 62(2): 519-524 (2013) - [j118]Rik Pintelon, Johan Schoukens:
FRF Measurement of Nonlinear Systems Operating in Closed Loop. IEEE Trans. Instrum. Meas. 62(5): 1334-1345 (2013) - [j117]Johan Schoukens, Gerd Vandersteen, Rik Pintelon, Zlatko Emedi, Yves Rolain:
Bounding the Polynomial Approximation Errors of Frequency Response Functions. IEEE Trans. Instrum. Meas. 62(5): 1346-1353 (2013) - [j116]Egon Geerardyn, Yves Rolain, Johan Schoukens:
Design of Quasi-Logarithmic Multisine Excitations for Robust Broad Frequency Band Measurements. IEEE Trans. Instrum. Meas. 62(5): 1364-1372 (2013) - [c30]Johan Schoukens, Yves Rolain, Gerd Vandersteen, Rik Pintelon:
Study of Small Data Set Efficiency Losses in System Identification: The FIR Case. ALCOSP 2013: 68-73 - [c29]Koen Tiels, Johan Schoukens:
Iterative Update of the Pole Locations in a Wiener-Schetzen Model. ALCOSP 2013: 366-371 - [c28]Anna Marconato, Johan Schoukens:
Study of User-Specified Parameters in Nonlinear Dynamics Modeling with Neural Networks. ALCOSP 2013: 593-598 - [c27]Anna Marconato, Maarten Schoukens, Yves Rolain, Johan Schoukens:
Study of the effective number of parameters in nonlinear identification benchmarks. CDC 2013: 4308-4313 - [c26]Alexander De Cock, Michel Gevers, Johan Schoukens:
A preliminary study on optimal input design for nonlinear systems. CDC 2013: 4931-4936 - [c25]Koen Tiels, Johan Schoukens:
From coupled to decoupled polynomial representations in parallel Wiener-Hammerstein models. CDC 2013: 4937-4942 - [c24]Torbjörn Wigren, Johan Schoukens:
Three free data sets for development and benchmarking in nonlinear system identification. ECC 2013: 2933-2938 - 2012
- [j115]Jonas Sjöberg, Johan Schoukens:
Initializing Wiener-Hammerstein models based on partitioning of the best linear approximation. Autom. 48(2): 353-359 (2012) - [j114]David Rijlaarsdam, Tom Oomen, Pieter Nuij, Johan Schoukens, Maarten Steinbuch:
Uniquely connecting frequency domain representations of given order polynomial Wiener-Hammerstein systems. Autom. 48(9): 2381-2384 (2012) - [j113]David T. Westwick, Johan Schoukens:
Initial estimates of the linear subsystems of Wiener-Hammerstein models. Autom. 48(11): 2931-2936 (2012) - [j112]Miroslav Zivanovic, Johan Schoukens:
Single and Piecewise Polynomials for Modeling of Pitched Sounds. IEEE Trans. Speech Audio Process. 20(4): 1270-1281 (2012) - [j111]Hin Kwan Wong, Johan Schoukens, Keith R. Godfrey:
Analysis of Best Linear Approximation of a Wiener-Hammerstein System for Arbitrary Amplitude Distributions. IEEE Trans. Instrum. Meas. 61(3): 645-654 (2012) - [j110]Johan Schoukens, Gerd Vandersteen, Yves Rolain, Rik Pintelon:
Frequency Response Function Measurements Using Concatenated Subrecords With Arbitrary Length. IEEE Trans. Instrum. Meas. 61(10): 2682-2688 (2012) - [j109]Prasanth Thummala, Johan Schoukens:
Estimation of the FRF Through the Improved Local Bandwidth Selection in the Local Polynomial Method. IEEE Trans. Instrum. Meas. 61(10): 2833-2843 (2012) - [j108]Mikaya L. D. Lumori, Johan Schoukens, John Lataire:
Approximate ML Estimation of the Period and Spectral Content of Multiharmonic Signals Without User Interaction. IEEE Trans. Instrum. Meas. 61(11): 2953-2959 (2012) - [c23]Soma Tayamon, Torbjörn Wigren, Johan Schoukens:
Convergence analysis and experiments using an RPEM based on nonlinear ODEs and midpoint integration. CDC 2012: 2858-2865 - [c22]Michel Gevers, Matthias Caenepeel, Johan Schoukens:
Experiment design for the identification of a simple Wiener system. CDC 2012: 7333-7338 - [c21]Benjamin Sanchez, Gerd Vandersteen, Irene Martin, Diego Castillo, Alfons Torrego, Pere J. Riu, Johan Schoukens, Ramon Bragós:
Minimally invasive in vivo human lung tissue bioimpedance measurements during the bronchoscopy procedure. EMBC 2012: 130-133 - 2011
- [j107]David Rijlaarsdam, Pieter Nuij, Johan Schoukens, Maarten Steinbuch:
Spectral analysis of block structured nonlinear systems and higher order sinusoidal input describing functions. Autom. 47(12): 2684-2688 (2011) - [j106]Maite Bauwens, Henrik Ohlsson, Kurt Barbé, Veerle Beelaerts, Frank Dehairs, Johan Schoukens:
On climate reconstruction using bivalves: Three methods to interpret the chemical signature of a shell. Comput. Methods Programs Biomed. 104(2): 104-111 (2011) - [j105]Miroslav Zivanovic, Johan Schoukens:
On The Polynomial Approximation for Time-Variant Harmonic Signal Modeling. IEEE Trans. Speech Audio Process. 19(3): 458-467 (2011) - [j104]Benjamin Sanchez, Johan Schoukens, Ramon Bragós, Gerd Vandersteen:
Novel Estimation of the Electrical Bioimpedance Using the Local Polynomial Method. Application to In Vivo Real-Time Myocardium Tissue Impedance Characterization During the Cardiac Cycle. IEEE Trans. Biomed. Eng. 58(12): 3376-3385 (2011) - [j103]Kurt Barbé, Rik Pintelon, Johan Schoukens, Lieve Lauwers:
Improved Variance Estimates of FRF Measurements in the Presence of Nonlinear Distortions Via Overlap. IEEE Trans. Instrum. Meas. 60(1): 300-309 (2011) - [j102]Kurt Barbé, Johan Schoukens, Rik Pintelon:
The Use of Nonparametric Noise Models Extracted From Overlapping Subrecords for System Identification. IEEE Trans. Signal Process. 59(10): 4635-4647 (2011) - [c20]David Rijlaarsdam, Pieter Nuij, Johan Schoukens, Maarten Steinbuch:
Frequency domain based friction compensation - Industrial application to transmission electron microscopes -. ACC 2011: 4093-4098 - [c19]Clara M. Ionescu, Johan Schoukens, Robin De Keyser:
Detecting and analyzing non-linear effects in respiratory impedance measurements. ACC 2011: 5412-5417 - [c18]Johan Schoukens, Yves Rolain, Gerd Vandersteen, Rik Pintelon:
User friendly Box-Jenkins identification using nonparametric noise models. CDC/ECC 2011: 2148-2153 - [c17]Michel Gevers, Rik Pintelon, Johan Schoukens:
The Local Polynomial Method for nonparametric system identification: Improvements and experimentation. CDC/ECC 2011: 4302-4307 - [c16]Koen Tiels, Johan Schoukens:
Identifying a Wiener system using a variant of the Wiener G-Functionals. CDC/ECC 2011: 5780-5785 - [c15]Laurent Vanbeylen, Anne Van Mulders, Johan Schoukens:
A state-space view on locally-stable, globally-unstable nonlinear models driven by Gaussian burst inputs. CDC/ECC 2011: 6060-6065 - [c14]Miroslav Zivanovic, Johan Schoukens:
Constrained time-variant signal modeling for identifying colliding harmonics in sound mixtures. EUSIPCO 2011: 699-703 - 2010
- [j101]Johan Paduart, Lieve Lauwers, Jan Swevers, Kris Smolders, Johan Schoukens, Rik Pintelon:
Identification of nonlinear systems using Polynomial Nonlinear State Space models. Autom. 46(4): 647-656 (2010) - [j100]Torsten Söderström, Mei Hong, Johan Schoukens, Rik Pintelon:
Accuracy analysis of time domain maximum likelihood method and sample maximum likelihood method for errors-in-variables and output error identification. Autom. 46(4): 721-727 (2010) - [j99]Anne Van Mulders, Johan Schoukens, Marnix Volckaert, Moritz Diehl:
Two nonlinear optimization methods for black box identification compared. Autom. 46(10): 1675-1681 (2010) - [j98]Johan Schoukens, Tadeusz P. Dobrowiecki, Yves Rolain, Rik Pintelon:
Upper Bounding Variations of Best Linear Approximations of Nonlinear Systems in Power Sweep Measurements. IEEE Trans. Instrum. Meas. 59(5): 1141-1148 (2010) - [j97]Johan Schoukens, Kurt Barbé, Laurent Vanbeylen, Rik Pintelon:
Nonlinear Induced Variance of Frequency Response Function Measurements. IEEE Trans. Instrum. Meas. 59(9): 2468-2474 (2010) - [j96]Johan Schoukens, Rik Pintelon:
Study of the Variance of Parametric Estimates of the Best Linear Approximation of Nonlinear Systems. IEEE Trans. Instrum. Meas. 59(12): 3159-3167 (2010) - [j95]Kurt Barbé, Rik Pintelon, Johan Schoukens:
Welch method revisited: nonparametric power spectrum estimation via circular overlap. IEEE Trans. Signal Process. 58(2): 553-565 (2010) - [c13]Johan Schoukens, Yves Rolain, Rik Pintelon:
On the use of parametric and non-parametric noise-models in time- and frequency domain system identification. CDC 2010: 316-321 - [c12]Tillmann Falck, Johan A. K. Suykens, Johan Schoukens, Bart De Moor:
Nuclear norm regularization for overparametrized Hammerstein systems. CDC 2010: 7202-7207 - [c11]Miroslav Zivanovic, Johan Schoukens:
Time-variant harmonic and transient signal modeling by joint polynomial and piecewise linear approximation. EUSIPCO 2010: 467-471
2000 – 2009
- 2009
- [j94]Johan Schoukens, Gerd Vandersteen, Kurt Barbé, Rik Pintelon:
Nonparametric Preprocessing in System Identification: a Powerful Tool. Eur. J. Control 15(3-4): 260-274 (2009) - [j93]Gerd Vandersteen, Yves Rolain, Koen Vandermot, Rik Pintelon, Johan Schoukens, Wendy Van Moer:
Quasi-Analytical Bit-Error-Rate Analysis Technique Using Best Linear Approximation Modeling. IEEE Trans. Instrum. Meas. 58(2): 475-482 (2009) - [j92]Johan Schoukens, John Lataire, Rik Pintelon, Gerd Vandersteen, Tadeusz P. Dobrowiecki:
Robustness Issues of the Best Linear Approximation of a Nonlinear System. IEEE Trans. Instrum. Meas. 58(5): 1737-1745 (2009) - [j91]Johan Schoukens, Rik Pintelon:
Estimation of Nonparametric Noise Models for Linear Dynamic Systems. IEEE Trans. Instrum. Meas. 58(8): 2468-2474 (2009) - [j90]Jérôme Antoni, Johan Schoukens:
Optimal Settings for Measuring Frequency Response Functions With Weighted Overlapped Segment Averaging. IEEE Trans. Instrum. Meas. 58(9): 3276-3287 (2009) - [j89]Laurent Vanbeylen, Rik Pintelon, Johan Schoukens:
Blind maximum-likelihood identification of wiener systems. IEEE Trans. Signal Process. 57(8): 3017-3029 (2009) - [c10]Johan Schoukens, Gerd Vandersteen, Kurt Barbé, Rik Pintelon:
Nonparametric preprocessing in system identification: A powerful tool. ECC 2009: 1-14 - [c9]Miroslav Zivanovic, Johan Schoukens:
Time-variant harmonic signal modeling by using polynomial approximation and fully automated spectral analysis. EUSIPCO 2009: 899-903 - 2008
- [j88]Johan Schoukens, Rik Pintelon, Martin Enqvist:
Study of the LTI relations between the outputs of two coupled Wiener systems and its application to the generation of initial estimates for Wiener-Hammerstein systems. Autom. 44(7): 1654-1665 (2008) - [j87]Laurent Vanbeylen, Rik Pintelon, Johan Schoukens:
Blind maximum likelihood identification of Hammerstein systems. Autom. 44(12): 3139-3146 (2008) - [j86]Anouk de Brauwere, Fjo De Ridder, Rik Pintelon, Jeroen Meersmans, Johan Schoukens, Frank Dehairs:
Identification of a periodic time series from an environmental proxy record. Comput. Geosci. 34(12): 1781-1790 (2008) - [j85]Yves Rolain, Wendy Van Moer, Johan Schoukens, Tom Dhaene:
Estimation and Validation of Semiparametric Dynamic Nonlinear Models. IEEE Trans. Instrum. Meas. 57(2): 395-400 (2008) - [j84]Kurt Barbé, Johan Schoukens, Rik Pintelon:
Frequency-Domain, Errors-in-Variables Estimation of Linear Dynamic Systems Using Data From Overlapping Subrecords. IEEE Trans. Instrum. Meas. 57(8): 1529-1536 (2008) - [j83]Johan Schoukens, Liesbeth Gommé, Wendy Van Moer, Yves Rolain:
Identification of a Block-Structured Nonlinear Feedback System, Applied to a Microwave Crystal Detector. IEEE Trans. Instrum. Meas. 57(8): 1734-1740 (2008) - [j82]Laurent Vanbeylen, Rik Pintelon, Johan Schoukens:
Application of Blind Identification to Nonlinear Calibration. IEEE Trans. Instrum. Meas. 57(8): 1771-1778 (2008) - [j81]Lieve Lauwers, Johan Schoukens, Rik Pintelon, Martin Enqvist:
A Nonlinear Block Structure Identification Procedure Using Frequency Response Function Measurements. IEEE Trans. Instrum. Meas. 57(10): 2257-2264 (2008) - 2007
- [j80]Rik Pintelon, Johan Schoukens:
Frequency domain maximum likelihood estimation of linear dynamic errors-in-variables models. Autom. 43(4): 621-630 (2007) - [j79]Rik Pintelon, Johan Schoukens, Patrick Guillaume:
Box-Jenkins identification revisited - Part III: Multivariable systems. Autom. 43(5): 868-875 (2007) - [j78]Johan Schoukens, Widanalage Dhammika Widanage, Keith R. Godfrey, Rik Pintelon:
Initial estimates for the dynamics of a Hammerstein system. Autom. 43(7): 1296-1301 (2007) - [j77]Jérôme Antoni, Johan Schoukens:
A comprehensive study of the bias and variance of frequency-response-function measurements: Optimal window selection and overlapping strategies. Autom. 43(10): 1723-1736 (2007) - [j76]Tadeusz P. Dobrowiecki, Johan Schoukens:
Measuring a linear approximation to weakly nonlinear MIMO systems. Autom. 43(10): 1737-1751 (2007) - [j75]Tadeusz P. Dobrowiecki, Johan Schoukens:
Linear Approximation of Weakly Nonlinear MIMO Systems. IEEE Trans. Instrum. Meas. 56(3): 887-894 (2007) - [j74]Yves Rolain, Wendy Van Moer, Johan Schoukens, Rik Pintelon:
Measuring Nonlinear Differential RF Amplifiers Using One Single-Ended Source. IEEE Trans. Instrum. Meas. 56(3): 1042-1048 (2007) - [j73]Johan Paduart, Johan Schoukens, Yves Rolain:
Fast Measurement of Quantization Distortions in DSP Algorithms. IEEE Trans. Instrum. Meas. 56(5): 1917-1923 (2007) - 2006
- [j72]Johan Schoukens, Yves Rolain, Rik Pintelon:
Analysis of windowing/leakage effects in frequency response function measurements. Autom. 42(1): 27-38 (2006) - [j71]Rik Pintelon, Johan Schoukens:
Box-Jenkins identification revisited - Part I: Theory. Autom. 42(1): 63-75 (2006) - [j70]Rik Pintelon, Yves Rolain, Johan Schoukens:
Box-Jenkins identification revisited - Part II: Applications. Autom. 42(1): 77-84 (2006) - [j69]Kaushik Mahata, Rik Pintelon, Johan Schoukens:
On Parameter Estimation Using Nonparametric Noise Models. IEEE Trans. Autom. Control. 51(10): 1602-1612 (2006) - [j68]Tadeusz P. Dobrowiecki, Johan Schoukens, Patrick Guillaume:
Optimized Excitation Signals for MIMO Frequency Response Function Measurements. IEEE Trans. Instrum. Meas. 55(6): 2072-2079 (2006) - [j67]Rik Pintelon, Johan Schoukens, Patrick Guillaume:
Continuous-Time Noise Modeling From Sampled Data. IEEE Trans. Instrum. Meas. 55(6): 2253-2258 (2006) - [j66]Johan Schoukens, Yves Rolain, Rik Pintelon:
Leakage Reduction in Frequency-Response Function Measurements. IEEE Trans. Instrum. Meas. 55(6): 2286-2291 (2006) - [c8]Tom Coen, Johan Paduart, Jan Anthonis, Johan Schoukens, Josse De Baerdemaeker:
Nonlinear system identification on a combine harvester. ACC 2006: 1-6 - 2005
- [j65]Johan Schoukens, Rik Pintelon, Tadeusz P. Dobrowiecki, Yves Rolain:
Identification of linear systems with nonlinear distortions. Autom. 41(3): 491-504 (2005) - [j64]Emad Abd-Elrady, Johan Schoukens:
Least-squares periodic signal modeling using orbits of nonlinear ODEs and fully automated spectral analysis. Autom. 41(5): 857-862 (2005) - [j63]Philippe Crama, Johan Schoukens:
Computing an initial estimate of a Wiener-Hammerstein system with a random phase multisine excitation. IEEE Trans. Instrum. Meas. 54(1): 117-122 (2005) - [j62]Fjo De Ridder, Rik Pintelon, Johan Schoukens, David Paul Gillikin:
Modified AIC and MDL model selection criteria for short data records. IEEE Trans. Instrum. Meas. 54(1): 144-150 (2005) - [j61]Fjo De Ridder, Rik Pintelon, Johan Schoukens, Anouk Verheyden:
Reduction of the Gibbs phenomenon applied on nonharmonic time base distortions. IEEE Trans. Instrum. Meas. 54(3): 1118-1125 (2005) - [j60]Tom D'haene, Rik Pintelon, Johan Schoukens, Els Van Gheem:
Variance analysis of frequency response function measurements using periodic excitations. IEEE Trans. Instrum. Meas. 54(4): 1452-1456 (2005) - [j59]Rik Pintelon, Johan Schoukens, Laurence Pauwels, Els Van Gheem:
Diffusion systems: stability, modeling, and identification. IEEE Trans. Instrum. Meas. 54(5): 2061-2067 (2005) - 2004
- [j58]Philippe Crama, Johan Schoukens, Rik Pintelon:
Generation of enhanced initial estimates for Hammerstein Systems. Autom. 40(7): 1269-1273 (2004) - [j57]Johan Schoukens, Tadeusz P. Dobrowiecki, Rik Pintelon:
Estimation of the risk for an unstable behaviour of feedback systems in the presence of nonlinear distortions. Autom. 40(7): 1275-1279 (2004) - [j56]Philippe Crama, Johan Schoukens:
Hammerstein-Wiener system estimator initialization. Autom. 40(9): 1543-1550 (2004) - [j55]Johan Schoukens, Rik Pintelon, Yves Rolain:
Box-Jenkins alike identification using nonparametric noise models. Autom. 40(12): 2083-2089 (2004) - [j54]Rik Pintelon, Johan Schoukens:
Discussion on: "Identification of Multivariable Models of Fast Ferries". Eur. J. Control 10(2): 199-202 (2004) - [j53]Yves Rolain, Wendy Van Moer, Gerd Vandersteen, Johan Schoukens:
Why are nonlinear microwave systems measurements so involved? IEEE Trans. Instrum. Meas. 53(3): 726-729 (2004) - [j52]Rik Pintelon, Gerd Vandersteen, Ludwig De Locht, Yves Rolain, Johan Schoukens:
Experimental characterization of operational amplifiers: a system identification Approach-part I: theory and Simulations. IEEE Trans. Instrum. Meas. 53(3): 854-862 (2004) - [j51]Rik Pintelon, Yves Rolain, Gerd Vandersteen, Johan Schoukens:
Experimental characterization of operational amplifiers: a system identification approach-part II: calibration and measurements. IEEE Trans. Instrum. Meas. 53(3): 863-876 (2004) - [j50]Johan Schoukens, József G. Nemeth, Gerd Vandersteen, Rik Pintelon, Philippe Crama:
Linearization of nonlinear dynamic systems. IEEE Trans. Instrum. Meas. 53(4): 1245-1248 (2004) - [c7]Johan Schoukens, Rik Pintelon, Yves Rolain:
Time domain identification, frequency domain identification. Equivalencies! Differences? ACC 2004: 661-666 - [c6]Kaushik Mahata, Rik Pintelon, Johan Schoukens:
Frequency domain identification using non-parametric noise models. CDC 2004: 821-826 - 2003
- [j49]Johan Schoukens, József G. Nemeth, Philippe Crama, Yves Rolain, Rik Pintelon:
Fast approximate identification of nonlinear systems. Autom. 39(7): 1267-1274 (2003) - [j48]Rik Pintelon, Johan Schoukens, Yves Rolain:
Uncertainty of transfer function modelling using prior estimated noise models. Autom. 39(10): 1721-1733 (2003) - [j47]Alain Geens, Yves Rolain, Wendy Van Moer, Kenneth Vanhoenacker, Johan Schoukens:
Discussion on fundamental issues of NPR measurements. IEEE Trans. Instrum. Meas. 52(1): 197-202 (2003) - [j46]Kenneth Vanhoenacker, Johan Schoukens:
Detection of nonlinear distortions with multisine excitations in the case of nonideal behavior of the input signal. IEEE Trans. Instrum. Meas. 52(3): 748-753 (2003) - [j45]Johan Schoukens, Yves Rolain, Gyula Simon, Rik Pintelon:
Fully automated spectral analysis of periodic signals. IEEE Trans. Instrum. Meas. 52(4): 1021-1024 (2003) - 2002
- [j44]Johan Schoukens, Yves Rolain, Rik Pintelon:
Modified AIC rule for model selection in combination with prior estimated noise models. Autom. 38(5): 903-906 (2002) - [j43]Rik Pintelon, Johan Schoukens:
Some peculiarities of identification in the presence of model errors. Autom. 38(10): 1683-1693 (2002) - [j42]Wendy Van Moer, Yves Rolain, Johan Schoukens:
An automatic harmonic selection scheme for measurements and calibration with the nonlinear vectorial network analyzer. IEEE Trans. Instrum. Meas. 51(2): 337-341 (2002) - [j41]Gyula Simon, Rik Pintelon, László Sujbert, Johan Schoukens:
An efficient nonlinear least square multisine fitting algorithm. IEEE Trans. Instrum. Meas. 51(4): 750-755 (2002) - [j40]József G. Nemeth, István Kollár, Johan Schoukens:
Identification of Volterra kernels using interpolation. IEEE Trans. Instrum. Meas. 51(4): 770-775 (2002) - [j39]Johan Schoukens, Rik Pintelon, Tadeusz P. Dobrowiecki:
Linear modeling in the presence of nonlinear distortions. IEEE Trans. Instrum. Meas. 51(4): 786-792 (2002) - [c5]Koen Maertens, Johan Schoukens, Koen Deprez, Josse De Baerdemaeker:
Development of a smart mass flow sensor based on adaptive notch filtering and frequency domain identification. ACC 2002: 4359-4364 - 2001
- [j38]Johan Schoukens, Rik Pintelon, Yves Rolain, Tadeusz P. Dobrowiecki:
Frequency response function measurements in the presence of nonlinear distortions. Autom. 37(6): 939-946 (2001) - [j37]Rudi Vuerinckx, Rik Pintelon, Johan Schoukens, Yves Rolain:
Obtaining accurate confidence regions for the estimated zeros and poles in system identification problems. IEEE Trans. Autom. Control. 46(4): 656-659 (2001) - [j36]Tadeusz P. Dobrowiecki, Johan Schoukens:
Practical choices in the FRF measurement in presence of nonlinear distortions. IEEE Trans. Instrum. Meas. 50(1): 2-7 (2001) - [j35]Rik Pintelon, Johan Schoukens, Wendy Van Moer, Yves Rolain:
Identification of linear systems in the presence of nonlinear distortions. IEEE Trans. Instrum. Meas. 50(4): 855-863 (2001) - [j34]Kenneth Vanhoenacker, Tadeusz P. Dobrowiecki, Johan Schoukens:
Design of multisine excitations to characterize the nonlinear distortions during FRF-measurements. IEEE Trans. Instrum. Meas. 50(5): 1097-1102 (2001) - [j33]Balázs Vargha, Johan Schoukens, Yves Rolain:
Static nonlinearity testing of digital-to-analog converters. IEEE Trans. Instrum. Meas. 50(5): 1283-1288 (2001) - [j32]Gerd Vandersteen, Yves Rolain, Johan Schoukens:
An identification technique for data acquisition characterization in the presence of nonlinear distortions and time base distortions. IEEE Trans. Instrum. Meas. 50(5): 1355-1363 (2001) - [j31]Rik Pintelon, Johan Schoukens:
Measurement of frequency response functions using periodic excitations, corrupted by correlated input/output errors. IEEE Trans. Instrum. Meas. 50(6): 1753-1760 (2001) - [j30]Philippe Crama, Johan Schoukens:
Initial estimates of Wiener and Hammerstein systems using multisine excitation. IEEE Trans. Instrum. Meas. 50(6): 1791-1795 (2001) - [c4]Johan Schoukens, Rik Pintelon, Tadeusz P. Dobrowiecki:
Nonparametric model error bounds for control design in the presence of nonlinear distortions. CDC 2001: 2998-3003 - [c3]Adhemar Bultheel, Marc Van Barel, Yves Rolain, Johan Schoukens:
Robust rational approximation for identification. CDC 2001: 4770-4775 - [c2]Gerd Vandersteen, Piet Wambacq, Yves Rolain, Johan Schoukens, Stéphane Donnay, Marc Engels, Ivo Bolsens:
Efficient bit-error-rate estimation of multicarrier transceivers. DATE 2001: 164-168 - 2000
- [j29]Rik Pintelon, Johan Schoukens, Yves Rolain:
Box-Jenkins continuous-time modeling. Autom. 36(7): 983-991 (2000) - [j28]Rik Pintelon, Johan Schoukens:
Frequency domain system identification with missing data. IEEE Trans. Autom. Control. 45(2): 364-369 (2000) - [j27]Gyula Simon, Johan Schoukens:
Robust broadband periodic excitation design. IEEE Trans. Instrum. Meas. 49(2): 270-274 (2000) - [j26]Johan Schoukens, Rik Pintelon, Yves Rolain:
Broadband versus stepped sine FRF measurements. IEEE Trans. Instrum. Meas. 49(2): 275-278 (2000) - [j25]Jürgen Van Gorp, Johan Schoukens, Rik Pintelon:
Learning neural networks with noisy inputs using the errors-in-variables approach. IEEE Trans. Neural Networks Learn. Syst. 11(2): 402-414 (2000)
1990 – 1999
- 1999
- [j24]Johan Schoukens, Rik Pintelon, Yves Rolain:
Study of conditional ML estimators in time and frequency-domain system identification. Autom. 35(1): 91-100 (1999) - [j23]Johan Schoukens, Gerd Vandersteen, Rik Pintelon, Patrick Guillaume:
Frequency-domain identification of linear systems using arbitrary excitations and a nonparametric noise model. IEEE Trans. Autom. Control. 44(2): 343-347 (1999) - [j22]Rik Pintelon, Johan Schoukens, Gerd Vandersteen, Yves Rolain:
Identification of invariants of (over)parameterized models: finite sample results. IEEE Trans. Autom. Control. 44(5): 1073-1077 (1999) - [j21]Gerd Vandersteen, Johan Schoukens:
Measurement and identification of nonlinear systems consisting of linear dynamic blocks and one static nonlinearity. IEEE Trans. Autom. Control. 44(6): 1266-1271 (1999) - [j20]Rik Pintelon, Johan Schoukens:
Identification of continuous-time systems with missing data. IEEE Trans. Instrum. Meas. 48(3): 736-740 (1999) - [j19]Rik Pintelon, Johan Schoukens:
Time series analysis in the frequency domain. IEEE Trans. Signal Process. 47(1): 206-210 (1999) - 1998
- [j18]Johan Schoukens, Tadeusz P. Dobrowiecki, Rik Pintelon:
Parametric and nonparametric identification of linear systems in the presence of nonlinear distortions-a frequency domain approach. IEEE Trans. Autom. Control. 43(2): 176-190 (1998) - [j17]Dirk E. Torfs, Rudi Vuerinckx, Jan Swevers, Johan Schoukens:
Comparison of two feedforward design methods aiming at accurate trajectory tracking of the end point of a flexible robot arm. IEEE Trans. Control. Syst. Technol. 6(1): 2-14 (1998) - [j16]Johan Schoukens, Yves Rolain, Rik Pintelon:
Improved frequency response function measurements for random noise excitations. IEEE Trans. Instrum. Meas. 47(1): 322-326 (1998) - [j15]Patrick Guillaume, Rik Pintelon, Johan Schoukens:
A weighted total least squares estimator for multivariable systems with nearly maximum likelihood properties. IEEE Trans. Instrum. Meas. 47(4): 818-822 (1998) - [j14]Yves Rolain, Johan Schoukens, Gerd Vandersteen:
Signal reconstruction for non-equidistant finite length sample sets: a "KIS" approach. IEEE Trans. Instrum. Meas. 47(5): 1046-1052 (1998) - 1997
- [j13]Rik Pintelon, Johan Schoukens:
Identification of continuous-time systems using arbitrary signals. Autom. 33(5): 991-994 (1997) - [j12]Johan Schoukens, Rik Pintelon, Gerd Vandersteen, Patrick Guillaume:
Frequency-domain system identification using non-parametric noise models estimated from a small number of data sets. Autom. 33(6): 1073-1086 (1997) - [j11]Gerd Vandersteen, Yves Rolain, Johan Schoukens:
Non-parametric Estimation of the Frequency-response Functions of the Linear Blocks of a Wiener-Hammerstein Model. Autom. 33(7): 1351-1355 (1997) - [j10]Yves Rolain, Johan Schoukens, Rik Pintelon:
Order estimation for linear time-invariant systems using frequency domain identification methods. IEEE Trans. Autom. Control. 42(10): 1408-1417 (1997) - [j9]Rik Pintelon, Johan Schoukens, Gerd Vandersteen:
Frequency domain system identification using arbitrary signals. IEEE Trans. Autom. Control. 42(12): 1717-1720 (1997) - [j8]Rik Pintelon, Johan Schoukens, Gerd Vandersteen:
Model selection through a statistical analysis of the global minimum of a weighted nonlinear least squares cost function. IEEE Trans. Signal Process. 45(3): 686-693 (1997) - 1996
- [j7]Rik Pintelon, Johan Schoukens, Tomas McKelvey, Yves Rolain:
Minimum variance bounds for overparameterized models. IEEE Trans. Autom. Control. 41(5): 719-720 (1996) - [j6]Rudi Vuerinckx, Yves Rolain, Johan Schoukens, Rik Pintelon:
Design of stable IIR filters in the complex domain by automatic delay selection. IEEE Trans. Signal Process. 44(9): 2339-2344 (1996) - [c1]Rudi Vuerinckx, Yves Rolain, Johan Schoukens, Rik Pintelon:
Design of stable IIR filters in the complex domain by automatic delay selection. ICASSP 1996: 1379-1382 - 1995
- [j5]Patrick Guillaume, Rik Pintelon, Johan Schoukens:
Robust parametric transfer function estimation using complex logarithmic frequency response data. IEEE Trans. Autom. Control. 40(7): 1180-1190 (1995) - 1994
- [j4]Johan Schoukens, Rik Pintelon, Hugo Van hamme:
Identification of linear dynamic systems using piecewise constant excitations: Use, misuse and alternatives. Autom. 30(7): 1153-1169 (1994) - [j3]Johan Schoukens, Rik Pintelon:
Quantifying model errors of identified transfer functions. IEEE Trans. Autom. Control. 39(8): 1733-1737 (1994) - [j2]Rik Pintelon, Patrick Guillaume, Yves Rolain, Johan Schoukens, Hugo Van hamme:
Parametric identification of transfer functions in the frequency domain-a survey. IEEE Trans. Autom. Control. 39(11): 2245-2260 (1994) - 1990
- [j1]Johan Schoukens:
Modeling of continuous time systems using a discrete time representation. Autom. 26(3): 579-583 (1990)
Coauthor Index
[j160] [i28] [i24] [i23] [j134] [c32] [j122] [j120] [j118] [j117] [c30] [j110] [j103] [j102] [c18] [c17] [j101] [j100] [j98] [j97] [j96] [j95] [c13] [j94] [j93] [j92] [j91] [j89] [c10] [j88] [j87] [j86] [j84] [j82] [j81] [j80] [j79] [j78] [j74] [j72] [j71] [j70] [j69] [j67] [j66] [j65] [j62] [j61] [j60] [j59] [j58] [j57] [j55] [j54] [j52] [j51] [j50] [c7] [c6] [j49] [j48] [j45] [j44] [j43] [j41] [j39] [j38] [j37] [j35] [j31] [c4] [j29] [j28] [j26] [j25] [j24] [j23] [j22] [j20] [j19] [j18] [j16] [j15] [j13] [j12] [j10] [j9] [j8] [j7] [j6] [c1] [j5] [j4] [j3] [j2]
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