9 citations · 47 across the 37 of their papers we have counts for
6 papers · 1 filter
Snapshot-driven Rational Interpolation of Parametric Systems
Art J. R. Pelling, Karim Cherifi, Ion Victor Gosea +1
Parametric data-driven modeling is relevant for many applications in which the model depends on parameters that can potentially vary in both space and time. In this paper, we prese…
Implicit and explicit matching of non-proper transfer functions in the Loewner framework
Ion Victor Gosea, Jan Heiland
The reduced-order modeling of a system from data (also known as system identification) is a classical task in system and control theory and well understood for standard linear syst…
Data-driven quadratic modeling in the Loewner framework from input-output time-domain measurements
D. S. Karachalios, I. V. Gosea, L. Gkimisis +1
In this study, we present a purely data-driven method that uses the Loewner framework (LF) along with nonlinear optimization techniques to infer quadratic with affine control dynam…
Bilinear realization from input-output data with neural networks
Dimitrios S. Karachalios, Ion Victor Gosea, Kirandeep Kour +1
We present a method that connects a well-established nonlinear (bilinear) identification method from time-domain data with neural network (NNs) advantages. The main challenge for f…
Model reduction of linear hybrid systems
Ion Victor Gosea, Mihaly Petreczky, John Leth +2
The paper proposes a model reduction algorithm for linear hybrid systems, i.e., hybrid systems with externally induced discrete events, with linear continuous subsystems, and linea…
On Bilinear Time Domain Identification and Reduction in the Loewner Framework
D. S. Karachalios, I. V. Gosea, A. C. Antoulas
The Loewner framework-(LF) in combination with Volterra series-(VS) offers a non-intrusive approximation method that is capable of identifying bilinear models from time-domain meas…