82 citations · 238 across the 7 of their papers we have counts for
7 papers · 1 filter
Data driven discrete-time parsimonious identification of a nonlinear state-space model for a weakly nonlinear system with short data record
Rishi Relan, Koen Tiels, Anna Marconato +2
Many real world systems exhibit a quasi linear or weakly nonlinear behavior during normal operation, and a hard saturation effect for high peaks of the input signal. In this paper,…
Regularized Nonparametric Volterra Kernel Estimation
Georgios Birpoutsoukis, Anna Marconato, John Lataire +1
In this paper, the regularization approach introduced recently for nonparametric estimation of linear systems is extended to the estimation of nonlinear systems modelled as Volterr…
Improved Initialization for Nonlinear State-Space Modeling
A. Marconato, J. Sjöberg, J. A. K. Suykens +1
This paper discusses a novel initialization algorithm for the estimation of nonlinear state-space models. Good initial values for the model parameters are obtained by identifying s…
Nonlinear system modeling based on constrained Volterra series estimates
P. Śliwiński, A. Marconato, P. Wachel +1
A simple nonlinear system modeling algorithm designed to work with limited \emph{a priori }knowledge and short data records, is examined. It creates an empirical Volterra series-ba…
Comparison of several data-driven nonlinear system identification methods on a simplified glucoregulatory system example
Anna Marconato, Maarten Schoukens, Koen Tiels +3
In this paper, several advanced data-driven nonlinear identification techniques are compared on a specific problem: a simplified glucoregulatory system modeling example. This probl…
Parametric identification of parallel Wiener-Hammerstein systems
Maarten Schoukens, Anna Marconato, Rik Pintelon +2
Block-oriented nonlinear models are popular in nonlinear modeling because of their advantages to be quite simple to understand and easy to use. To increase the flexibility of singl…
Filter-based regularisation for impulse response modelling
Anna Marconato, Maarten Schoukens, Johan Schoukens
In the last years, the success of kernel-based regularisation techniques in solving impulse response modelling tasks has revived the interest on linear system identification. In th…