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 review the state of affairs in the area of approximation of large-scale
systems. We distinguish three basic categories, namely the {SVD}-based, the {Krylov}-based …

We present a method in which the Padé approximant is used to calculate the asymptotic
behavior of a function from the first few terms of its power series. We illustrate this method by …

In today's technological world, physical and artificial processes are mainly described by
mathematical models, which can be used for simulation or control. These processes are …

The mathematical theory of Krylov subspace methods with a focus on solving systems of
linear algebraic equations is given a detailed treatment in this principles-based book …

This dissertation focuses on efficiently forming reduced-order models for large, linear
dynamic systems. Projections onto unions of Krylov subspaces lead to a class of reduced …

In recent years, a great deal of attention has been devoted to Krylov subspace techniques
for reduced-order modeling of large-scale dynamical systems. The surge of interest was …

An overview of model reduction methods and a comparison of the resulting algorithms is
presented. These approaches are divided into two broad categories, namely SVD based …

Iterative solution of linear systems Page 1 Ada Numerica (1991), pp. 57-100 Iterative solution of
linear systems Roland W. Preund * RIACS, Mail Stop Ellis Street NASA Ames Research Center …

This book is intended to be a treatise on the theory and modeling of secondorder stationary
processes with an exposition of some application areas which we believe are important in …