Model order reduction for strictly passive and causal distributed systems

  • Authors:
  • Luca Daniel;Joel Phillips

  • Affiliations:
  • University of California, Berkeley;Cadence Berkeley Labs

  • Venue:
  • Proceedings of the 39th annual Design Automation Conference
  • Year:
  • 2002

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Abstract

This paper presents a class of algorithms suitable for model reduction of distributed systems. Distributed systems are not suitable for treatment by standard model-reduction algorithms such as PRIMA, PVL, and the Arnoldi schemes because they generate matrices that are dependent on frequency (or other parameters) and cannot be put in a lumped or state-space form. Our algorithms build on well-known projection-based reduction techniques, and so require only matrix-vector product operations and are thus suitable for operation in conjunction with electromagnetic analysis codes that use iterative solution methods and fast-multipole acceleration techniques. Under the condition that the starting systems satisfy system-theoretic properties required of physical systems, the reduced systems can be guaranteed to be passive. For distributed systems, we argue that causality of the underlying representation is as important a consideration.