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 …

The paper describes the recent state of the art in hierarchical analog synthesis, with a strong
emphasis on associated techniques for computer-aided model generation and optimization …

Not only do modeling and simulation help provide a better understanding of how real-world
systems function, they also enable us to predict system behavior before a system is actually …

We present a projection-based nonlinear model order reduction method, named model
order reduction via quadratic-linear systems (QLMOR). QLMOR employs two novel ideas: 1) …

Well-designed circuits are one key ldquoinsulatingrdquo layer between the increasingly
unruly behavior of scaled complementary metal-oxide-semiconductor devices and the …

In this study we discuss the problem of Model Order Reduction (MOR) for a class of
nonlinear dynamical systems. In particular, we consider reduction schemes based on …

In this first section we present a high level discussion on computational science, and the
need for compact models of phenomena observed in nature and industry. We argue that …

This work presents a model reduction algorithm motivated by a connection between
frequency-domain projection methods and approximation of truncated balanced …

In this paper, we discuss the model order reduction problem for descriptor systems, that is,
systems with dynamics described by differential-algebraic equations. We focus on linear …

In this paper, we present a methodology for generating guaranteed passive time-domain
models of subsystems described by tabulated frequency-domain data obtained through …