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Reduced-Order Modeling of Linear Dynamical SystemsColloquium
|Speaker: ||Zhaojun Bai, University of Kentucky|
|Location: ||693 Kerr|
|Start time: ||Thu, Feb 4 1999, 4:10PM|
Krylov subspace methods, such as Lanczos and Arnoldi, are emerging
numerical techniques for reduced-order modeling of large scale
linear dynamical systems. Ths basic idea of reduced-order modeling
of a dynamical system is to replace the original system by a system
of the same type, but with much smaller state-space dimension. The
recent surge of interest in Krylov subspace methods was triggered by
the need of such techniques in the analysis and synthesis of large
scale dynamic systems, such as ones in intergrated electronic circuits
and structural dynamics.
In this talk, we will start with the basic ideas of reduced-order
modeling techniques and then describe Krylov subspace methods and
their connections with Pade approximation and other mathematical
theory. Furthermore, we will discuss the stability and passivity
(positive realness) of reduced-order models. Numerical examples from
large scale intergrated circuits simulation will be used for
demonstrating the applicability of these techniques.
Part of this work was carried out while the speaker was on sabbatical
at Bell Labs. during the 1997-1998 academic year.