44 citations · 75 across the 19 of their papers we have counts for
22 papers
Variable decoupling and the Kolmogorov Superposition Theorem for rational functions
A. C. Antoulas, I. V. Gosea, C. Poussot-Vassal
This work shows that for rational multivariate functions, the Kolmogorov Superposition Theorem (KST) involves several single-variable functions, which can be written down by inspec…
Rational approximation for Zolotarev sign and ratio problems
Charles Poussot-Vassal, Ion Victor Gosea, Athanasios C. Antoulas
We study algorithms for Zolotarev (3rd and 4th) problems rational approximation. First, we show that the Loewner framework (LF) is appropriate to rapidly and with no iterations, ap…
Tensor-based multivariate function approximation: methods benchmarking and comparison
Charles Poussot-Vassal, Ion Victor Gosea, Pierre Vuillemin +1
We evaluate some methods designed for tensor- (or data-) based multivariate model construction (approximation and compression). To this aim, a collection of multivariate functions…
On the Loewner framework, the Kolmogorov superposition theorem, and the curse of dimensionality
Athanasios C. Antoulas, Ion Victor Gosea, Charles Poussot-Vassal
The Loewner framework is an interpolatory approach for the approximation of linear and nonlinear systems. The purpose here is to extend this framework to linear parametric systems…
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…
A framework for fitting quadratic-bilinear systems with applications to models of electrical circuits
Dimitrios S. Karachalios, Ion Victor Gosea, Athanasios C. Antoulas
In this contribution, we propose a data-driven procedure to fit quadratic-bilinear surrogate models from data. Although the dynamics characterizing the original model are strongly…
Data-driven modeling and control of large-scale dynamical systems in the Loewner framework
Ion Victor Gosea, Charles Poussot-Vassal, Athanasios C. Antoulas
In this contribution, we discuss the modeling and model reduction framework known as the Loewner framework. This is a data-driven approach, applicable to large-scale systems, which…
Reduced-order modeling of LPV systems in the Loewner framework
Ion Victor Gosea, Mihaly Petreczky, Athanasios C. Antoulas
We propose a model reduction method for LPV systems. We consider LPV state-space representations with an affine dependence on the scheduling variables. The main idea behind the pro…
Factorization of the Loewner matrix pencil and its consequences
Qiang Zhang, Ion Victor Gosea, Athanasios C. Antoulas
This paper starts by deriving a factorization of the Loewner matrix pencil that appears in the data-driven modeling approach known as the Loewner framework and explores its consequ…
Learning reduced-order models of quadratic control systems from input-output data
Ion Victor Gosea, Dimitrios S. Karachalios, Athanasios C. Antoulas
In this paper, we address an extension of the Loewner framework for learning quadratic control systems from input-output data. The proposed method first constructs a reduced-order…
On Loewner data-driven control for infinite-dimensional systems
Ion Victor Gosea, Charles Poussot-Vassal, Athanasios C. Antoulas
In this paper, we address extensions of the Loewner Data-Driven Control (L-DDC) methodology. First, this approach is extended by incorporating two alternative approximation methods…
Rational approximation of the absolute value function from measurements: a numerical study of recent methods
Ion Victor Gosea, Athanasios C. Antoulas
In this work, we propose an extensive numerical study on approximating the absolute value function. The methods presented in this paper compute approximants in the form of rational…
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…
A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings
Mohammad Amin Khodkar, Pedram Hassanzadeh, Athanasios Antoulas
We introduce a data-driven method and shows its skills for spatiotemporal prediction of high-dimensional chaotic dynamics and turbulence. The method is based on a finite-dimensiona…
Case study: Approximations of the Bessel Function
D. S. Karachalios, I. V. Gosea, Q. Zhang +1
The purpose of this note is to compare various approximation methods as applied to the inverse of the Bessel function of the first kind, in a given domain of the complex plane.
Approximation of a damped Euler-Bernoulli beam model in the Loewner framework
Ion Victor Gosea, Athanasios C. Antoulas
The Loewner framework for model order reduction is applied to the class of infinite-dimension systems. The transfer function of such systems is irrational (as opposed to linear sys…
Data-driven model order reduction of linear switched systems
Ion Victor Gosea, Mihaly Petreczky, Athanasios C. Antoulas
The Loewner framework for model reduction is extended to the class of linear switched systems. One advantage of this framework is that it introduces a trade-off between accuracy an…
On the norm and iterative model order reduction of linear switched systems
Ion Victor Gosea, Athanasios C. Antoulas
A new definition of the norm for linear switched systems is introduced. It is based on appropriately defined time-domain kernels, or equivalently, on infinite contr…
Balanced truncation for linear switched systems
Ion Victor Gosea, Mihaly Petreczky, Athanasios C. Antoulas +1
We propose a model order reduction approach for balanced truncation of linear switched systems. Such systems switch among a finite number of linear subsystems or modes. We compute…
Interpolatory Weighted-H2 Model Reduction
Branimir Anic, Christopher A. Beattie, Serkan Gugercin +1
This paper introduces an interpolation framework for the weighted-H2 model reduction problem. We obtain a new representation of the weighted-H2 norm of SISO systems that provides n…