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

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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.

论文关键词:Lanczos algorithm,Arnoldi process,Linear dynamical system,VLSI interconnect,Transfer function,Padé approximation,Stability,Passivity,Positive real function

论文评审过程:Received 11 September 1999, Revised 9 December 1999, Available online 26 October 2000.

论文官网地址:https://doi.org/10.1016/S0377-0427(00)00396-4