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Model reduction methods based on Krylov subspaces

Published online by Cambridge University Press:  29 July 2003

Roland W. Freund
Affiliation:
Bell Laboratories, Lucent Technologies, Room 2C-525, Murray Hill, NJ 07974-0636, USA E-mail: freund@research.bell-labs.com
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Abstract

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In recent years, reduced-order modelling techniques based on Krylov-subspace iterations, especially the Lanczos algorithm and the Arnoldi process, have become popular tools for tackling the large-scale time-invariant linear dynamical systems that arise in the simulation of electronic circuits. This paper reviews the main ideas of reduced-order modelling techniques based on Krylov subspaces and describes some applications of reduced-order modelling in circuit simulation.

Type
Research Article
Copyright
© Cambridge University Press 2003