3 citations · 4 across the 7 of their papers we have counts for
7 papers
A non-intrusive data-based reformulation of a hybrid projection-based model reduction method
Ion Victor Gosea, Serkan Gugercin, Christopher Beattie
We present a novel data-driven reformulation of the iterative SVD-rational Krylov algorithm (ISRK), in its original formulation a Petrov-Galerkin (two-sided) projection-based itera…
A modified AAA algorithm for learning stable reduced-order models from data
Tommaso Bradde, Stefano Grivet-Talocia, Quirin Aumann +1
In recent years, the Adaptive Antoulas-Anderson AAA algorithm has established itself as the method of choice for solving rational approximation problems. Data-driven Model Order Re…
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 and low-rank implementations of Balanced Singular Perturbation Approximation
Björn Liljegren-Sailer, Ion Victor Gosea
Balanced Singular Perturbation Approximation (SPA) is a model order reduction method for linear time-invariant systems that guarantees asymptotic stability and for which there exis…
Practical challenges in data-driven interpolation: dealing with noise, enforcing stability, and computing realizations
Quirin Aumann, Ion Victor Gosea
In this contribution, we propose a detailed study of interpolation-based data-driven methods that are of relevance in the model reduction and also in the systems and control commun…
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…