Reduced-order modeling of large linear subcircuits via a block Lanczos algorithm
DAC '95 Proceedings of the 32nd annual ACM/IEEE Design Automation Conference
Efficient full-wave electromagnetic analysis via model-order reduction of fast integral transforms
DAC '96 Proceedings of the 33rd annual Design Automation Conference
Proceedings of the 38th annual Design Automation Conference
Guaranteed passive balancing transformations for model order reduction
Proceedings of the 39th annual Design Automation Conference
A convex programming approach to positive real rational approximation
Proceedings of the 2001 IEEE/ACM international conference on Computer-aided design
PRIMA: passive reduced-order interconnect macromodeling algorithm
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Analysis of interconnect networks using complex frequency hopping (CFH)
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Operator-based model-order reduction of linear periodically time-varying systems
Proceedings of the 42nd annual Design Automation Conference
pFFT in FastMaxwell: a fast impedance extraction solver for 3D conductor structures over substrate
Proceedings of the conference on Design, automation and test in Europe
QLMOR: a new projection-based approach for nonlinear model order reduction
Proceedings of the 2009 International Conference on Computer-Aided Design
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Complexity reduction for the design of interacting controllers
HSCC'07 Proceedings of the 10th international conference on Hybrid systems: computation and control
Passive reduced order modeling of multiport interconnects via semidefinite programming
Proceedings of the Conference on Design, Automation and Test in Europe
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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.