18 citations · 26 across the 4 of their papers we have counts for
14 papers
Applying Polynomial Decoupling Methods to the Polynomial NARX Model
Kiana Karami, David Westwick, Johan Schoukens
System identification uses measurements of a dynamic system's input and output to reconstruct a mathematical model for that system. These can be mechanical, electrical, physiologic…
A frequency domain approach for local module identification in dynamic networks
Karthik R. Ramaswamy, Péter Zoltán Csurcsia, Johan Schoukens +1
In classical approaches of dynamic network identification, in order to identify a system (module) embedded in a dynamic network, one has to formulate a Multi-input-Single-output (M…
PNLSS Toolbox 1.0
Jan Decuyper, Koen Tiels, Johan Schoukens
This is a demonstration of the PNLSS Toolbox 1.0. The toolbox is designed to identify polynomial nonlinear state-space models from data. Nonlinear state-space models can describe a…
Decoupling P-NARX models using filtered CPD
Jan Decuyper, David Westwick, Kiana Karami +1
Nonlinear Auto-Regressive eXogenous input (NARX) models are a popular class of nonlinear dynamical models. Often a polynomial basis expansion is used to describe the internal multi…
Decoupling multivariate functions using a non-parametric Filtered CPD approach
Jan Decuyper, Koen Tiels, Siep Weiland +1
Black-box model structures are dominated by large multivariate functions. Usually a generic basis function expansion is used, e.g. a polynomial basis, and the parameters of the fun…
A nonlinear model of vortex-induced forces on an oscillating cylinder in a fluid flow
Jan Decuyper, Tim De Troyer, Koen Tiels +2
A nonlinear model relating the imposed motion of a circular cylinder, submerged in a fluid flow, to the transverse force coefficient is presented. The nonlinear fluid system, featu…