DAC '95 Proceedings of the 32nd annual ACM/IEEE Design Automation Conference
Reduced-order modeling of large passive linear circuits by means of the SYPVL algorithm
Proceedings of the 1996 IEEE/ACM international conference on Computer-aided design
ICCAD '97 Proceedings of the 1997 IEEE/ACM international conference on Computer-aided design
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
PRIMA: passive reduced-order interconnect macromodeling algorithm
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Error bound for reduced system model by Pade approximation via the Lanczos process
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Efficient linear circuit analysis by Pade approximation via the Lanczos process
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Krylov subspace techniques for reduced-order modeling of large-scale dynamical systems
Applied Numerical Mathematics
Model order reduction of nonuniform transmission lines using integrated congruence transform
Proceedings of the 40th annual Design Automation Conference
Poor Man's TBR: A Simple Model Reduction Scheme
Proceedings of the conference on Design, automation and test in Europe - Volume 2
Interconnect Macromodelling and Approximation of Matrix Exponent
Analog Integrated Circuits and Signal Processing
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Krylov space methods initiated a new era for RLC circuit model order reduction. Although theoretically well-founded, these algorithms can fail to produce useful results for some types of circuits. In particular, controlling accuracy and ensuring passivity are required to fully utilize these algorithms in practice. In this paper we propose a methodology for passive reduction of RLC circuits based on extensions of PRIMA, that is both broad and practical. This work is made possible by uncovering the algebraic connections between this passive model order reduction algorithm and other Krylov space methods. In addition, a convergence criteria based on an error measure for PRIMA is presented as a first step towards intelligent order selection schemes. With these extensions and error criterion, examples demonstrate that accurate approximations are possible well into the RF frequency range even with expansions about s=0.