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

被引：299
|
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
收藏
页码：395 / 421
页数：27
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