An introduction to infinite-dimensional linear systems theory
An introduction to infinite-dimensional linear systems theory
Dynamic Thick Restarting of the Davidson, and the Implicitly Restarted Arnoldi Methods
SIAM Journal on Scientific Computing
Locking and Restarting Quadratic Eigenvalue Solvers
SIAM Journal on Scientific Computing
Approximation of Large-Scale Dynamical Systems (Advances in Design and Control) (Advances in Design and Control)
Parameterized model order reduction via a two-directional Arnoldi process
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Constructing Embedded Lattice Rules for Multivariate Integration
SIAM Journal on Scientific Computing
Convergence of the Dominant Pole Algorithm and Rayleigh Quotient Iteration
SIAM Journal on Matrix Analysis and Applications
Computing Transfer Function Dominant Poles of Large-Scale Second-Order Dynamical Systems
SIAM Journal on Scientific Computing
A two-directional Arnoldi process and its application to parametric model order reduction
Journal of Computational and Applied Mathematics
On dominant poles and model reduction of second order time-delay systems
Applied Numerical Mathematics
Interpolatory Projection Methods for Parameterized Model Reduction
SIAM Journal on Scientific Computing
PRIMA: passive reduced-order interconnect macromodeling algorithm
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Model Order Reduction of Parameterized Interconnect Networks via a Two-Directional Arnoldi 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
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Standard model order reduction techniques attempt to build reduced order models of large scale systems with similar input-output behavior over a wide range of input frequencies as the full system models. The method known as the dominant pole algorithm has previously been successfully used in combination with model order reduction techniques to approximate standard linear time-invariant dynamical systems and second order dynamical systems as well as nonlinear time-delay systems. In this paper, we show that the dominant pole algorithm can be adapted for parametric systems where these parameters usually have physical meaning. There are two approaches for finding dominant poles. These algorithms are illustrated by the second order numerical examples.