2012 - IEEE Joseph F. Keithley Award in Instrumentation and Measurement “For the development of innovative system identification methods for measurement applications.”
1998 - IEEE Fellow For fundamental research in frequency domain system identification and its application in instrumentation, control, and signal processing.
Control theory, System identification, Applied mathematics, Nonlinear system and Linear system are his primary areas of study. The Control theory study combines topics in areas such as Nonparametric statistics, Parametric statistics and Identification. His biological study spans a wide range of topics, including Structure, Errors-in-variables models, Frequency domain, Noise and Total least squares.
The study incorporates disciplines such as Time domain, Data mining, Parametric model, Algorithm and Process in addition to Frequency domain. His Applied mathematics research is multidisciplinary, relying on both Nonlinear control, Subspace topology and Estimation theory, Statistics, Estimator. His Linear approximation study in the realm of Nonlinear system connects with subjects such as Dielectric spectroscopy.
The scientist’s investigation covers issues in Control theory, Frequency domain, Nonlinear system, Algorithm and Identification. His Control theory research incorporates elements of Estimation theory, Noise measurement and System identification. His Frequency domain research integrates issues from Time domain, Transfer function, Parametric statistics, Estimator and Noise.
His Nonlinear system study combines topics from a wide range of disciplines, such as Nonlinear distortion, Electronic engineering, Linear model and Applied mathematics. His studies in Applied mathematics integrate themes in fields like Upper and lower bounds and Mathematical optimization. His research in Identification intersects with topics in Maximum likelihood and Artificial intelligence.
Rik Pintelon mainly investigates Control theory, Frequency response, Frequency domain, Nonlinear system and Identification. His studies deal with areas such as Errors-in-variables models, Applied mathematics and System identification as well as Control theory. His System identification study incorporates themes from Covariance and Parametric statistics.
His study in Frequency response is interdisciplinary in nature, drawing from both Nonparametric statistics, Missing data, Noise, Algorithm and Noise measurement. The various areas that he examines in his Frequency domain study include Time domain, Transfer function, Affine transformation and Differential equation. His Nonlinear system research includes elements of Nonlinear distortion, Representation, Linear model and Phase.
His scientific interests lie mostly in Control theory, Frequency response, Frequency domain, Nonparametric statistics and Nonlinear system. He has included themes like Algorithm, Errors-in-variables models, Noise and System identification in his Control theory study. His Frequency response research is multidisciplinary, incorporating elements of Frequency band, Noise, Electrical impedance, Electronic engineering and Approximation theory.
Rik Pintelon has researched Frequency domain in several fields, including Function, Transfer function, Estimator and Applied mathematics. His Applied mathematics study integrates concerns from other disciplines, such as Legendre polynomials and Calculus. His research integrates issues of Basis, Nonlinear distortion, Representation and Pole–zero plot in his study of Nonlinear system.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
System Identification: A Frequency Domain Approach
Rik Pintelon;Joannes Schoukens.
(2003)
Identification of Linear Systems: A Practical Guideline to Accurate Modeling
J. Schoukens;R. Pintelon.
(1991)
Parametric identification of transfer functions in the frequency domain-a survey
R. Pintelon;P. Guillaume;Y. Rolain;J. Schoukens.
IEEE Transactions on Automatic Control (1994)
The interpolated fast Fourier transform: a comparative study
J. Schoukens;R. Pintelon;H. Van Hamme.
instrumentation and measurement technology conference (1991)
Uncertainty bounds on modal parameters obtained from stochastic subspace identification
Edwin Reynders;Rik Pintelon;Guido De Roeck.
Mechanical Systems and Signal Processing (2008)
Parametric and nonparametric identification of linear systems in the presence of nonlinear distortions-a frequency domain approach
J. Schoukens;T. Dobrowiecki;R. Pintelon.
IEEE Transactions on Automatic Control (1998)
Crest-factor minimization using nonlinear Chebyshev approximation methods
P. Guillaume;J. Schoukens;R. Pintelon;I. Kollar.
IEEE Transactions on Instrumentation and Measurement (1991)
Identification of nonlinear systems using Polynomial Nonlinear State Space models
Johan Paduart;Lieve Lauwers;Jan Swevers;Kris Smolders.
Automatica (2010)
Identification of linear systems with nonlinear distortions
J. Schoukens;R. Pintelon;T. Dobrowiecki;Y. Rolain.
Automatica (2005)
An improved sine-wave fitting procedure for characterizing data acquisition channels
R. Pintelon;J. Schoukens.
instrumentation and measurement technology conference (1995)
Profile was last updated on December 6th, 2021.
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