Krylov-subspace methods for reduced-order modeling in circuit simulation

被引：307

作者：

Freund, RW ^{[1
]}

机构：

[1] Bell Labs, Lucent Technol, Murray Hill, NJ 07974 USA

来源：

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS | 2000年 / 123卷 / 1-2期

关键词：

Lanczos algorithm; Arnoldi process; linear dynamical system; VLSI interconnect; transfer function; Pade approximation; stability; passivity; positive real function;

D O I：

10.1016/S0377-0427(00)00396-4

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

The simulation of electronic circuits involves the numerical solution of very large-scale, sparse, in general nonlinear, systems of differential-algebraic equations. Often, the size of these systems can be reduced considerably by replacing the equations corresponding to linear subcircuits by approximate models of much smaller state-space dimension. In this paper, we describe the use of Krylov-subspace methods for generating such reduced-order models of linear subcircuits. Particular emphasis is on reduced-order modeling techniques that preserve the passivity of linear RLC subcircuits. (C) 2000 Elsevier Science B.V. All rights reserved.

引用

页码：395 / 421

页数：27

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