In the past decades, Model Order Reduction (MOR) has demonstrated its robustness and
wide applicability for simulating large-scale mathematical models in engineering and the …

In this paper, we investigate a recently introduced approach for nonlinear model order
reduction based on generalized moment matching. Using basic tensor calculus, we propose …

We introduce a data‐driven model order reduction approach that represents an extension of
the Loewner framework for linear and bilinear systems to the case of quadratic‐bilinear (QB) …

Many critical electronic design automation (EDA) problems suffer from the curse of
dimensionality, ie, the very fast-scaling computational burden produced by large number of …

This is a survey of model order reduction (MOR) methods based on momentmatching.
Moment-matching methods for linear non-parametric and parametric systems are reviewed …

This paper presents a new Riemannian modified Polak--Ribière--Polyak conjugate gradient
algorithm to construct the reduced systems of quadratic-bilinear systems. We eliminate the …

Research on nonlinear model order reduction has revealed that as nonlinearity increases,
the subspaces capturing dominant information require more complex bases. The complexity …

In this thesis we study structure-preserving model reduction methods for the efficient and
reliable approximation of dynamical systems. A major focus is the approximation of a …

Traditionally, model order reduction methods have been used to reduce the computational
complexity of mathematical models of dynamic systems, while preserving their functional …

We advance a recently proposed approach, called the associated transform, for computing
slim projection matrices serving high‐order Volterra transfer functions in the context of …