Oblique Projection Methods for Large Scale Model Reduction
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Decentralized and passive model order reduction of linear networks with massive ports
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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In this paper we present a model reduction algorithm that circumvents some of the issues encountered for parasitic networks with large numbers of input/output "ports". Our approach is based on the premise that for such networks, there are typically strong dependencies between the input waveforms at different network "ports". We present an approximate truncated balanced realizations procedure that, by exploiting such correlation information, produces much more compact models compared to standard algorithms such as PRIMA.