High-dimensional/high-fidelity nonlinear dynamical systems appear natura...
An essential tool in data-driven modeling of dynamical systems from freq...
We develop a unifying framework for interpolatory ℒ_2-optimal
reduced-or...
We provide a unifying framework for ℒ_2-optimal reduced-order
modeling f...
In this paper, we consider the structure-preserving model order reductio...
We consider the Bayesian approach to the linear Gaussian inference probl...
In this paper, we develop a structure-preserving formulation of the
data...
We present a novel reformulation of balanced truncation, a classical mod...
We present a novel projection-based model reduction framework for parame...
We extend the AAA (Adaptive-Antoulas-Anderson) algorithm to develop a
da...
We develop a structure-preserving parametric model reduction approach fo...
Contour integral methods for nonlinear eigenvalue problems seek to compu...
In this paper, we present an interpolation framework for structure-prese...
Nonlinear parametric inverse problems appear in many applications. Here,...
We consider linear dynamical systems with quadratic output. We first def...
In this paper, we extend the structure-preserving interpolatory model
re...
The AAA algorithm has become a popular tool for data-driven rational
app...
Driven by the need for describing and understanding wave propagation in
...
We consider the reduction of parametric families of linear dynamical sys...
We examine interpolatory model reduction methods that are well-suited fo...
We formulate here an approach to model reduction that is well-suited for...
Linear time-periodic (LTP) dynamical systems frequently appear in the
mo...