8 citations · 8 across the 2 of their papers we have counts for
5 papers
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 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…
Retrieving highly structured models starting from black-box nonlinear state-space models using polynomial decoupling
Jan Decuyper, Koen Tiels, Mark C. Runacres +1
Nonlinear state-space modelling is a very powerful black-box modelling approach. However powerful, the resulting models tend to be complex, described by a large number of parameter…
Deep Convolutional Networks in System Identification
Carl Andersson, Antônio H. Ribeiro, Koen Tiels +2
Recent developments within deep learning are relevant for nonlinear system identification problems. In this paper, we establish connections between the deep learning and the system…