Reduced-order modeling of large linear subcircuits via a block Lanczos algorithm
DAC '95 Proceedings of the 32nd annual ACM/IEEE Design Automation Conference
PRIMA: passive reduced-order interconnect macromodeling algorithm
ICCAD '97 Proceedings of the 1997 IEEE/ACM international conference on Computer-aided design
Model order reduction of nonuniform transmission lines using integrated congruence transform
Proceedings of the 40th annual Design Automation Conference
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Operator-based model-order reduction of linear periodically time-varying systems
Proceedings of the 42nd annual Design Automation Conference
SPRIM: structure-preserving reduced-order interconnect macromodeling
Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design
Projection-based approaches for model reduction of weakly nonlinear, time-varying systems
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
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Many subsystems encountered in communication systems can be modeled as linear periodic time-varyiing (LPTV) systems. In this paper, we present a novel structure preserving reduced-order modeling algorithm for LPTV systems. A key advance of our approach is that it preserves the periodic time-varying structure during the reduction process, thus resulting in reduced LPTV systems. Unlike prior LPTV model order reduction (MOR) techniques which recast the LPTV systems to artificial linear timeinvariant (LTI) systems and apply LTI MOR techniques for reduction, our structure preserving algorithm uses a time-varying projection directly on the original LPTV systems. Our approach always produces a smaller system than the original system, which was not valid for previous LPTV MOR techniques. We validate the proposed technique with several circuit examples, demonstrating significant size reductions and excellent accuracy.