The ongoing progress in transistor miniaturization and a continuous frequency increase are the main trends in the present day evolution of electronic circuits. A number of undesired effects are intrinsic to these developments and are suspected to be responsible for most of the flawed signals present in high frequency systems. Parasitic delays are thus introduced by the presence of interconnect lines and crosstalk due to coupling may lead to undesired switching events in transistor circuits. Accounting for the presence of interconnect lines, at a very early stage in the design flow has become unavoidable in recent years. However, time domain simulations of massively coupled interconnect networks may be computationally costly and have a tremendous impact on the overall duration of the design process. Replacing complex, high order circuit models by more compact surrogates is thus necessary. Model order reduction is an effective way to derive such surrogates. The final model must mimic certain aspects of the original model with sufficient accuracy and preserve the interconnect network’s most important properties. This approach enables designers to account for the undesired effects of interconnect lines such as, delays, rise-times and overshoots while maintaining the overall duration of time-domain simulations within acceptable limits. The aim of this thesis is to create a new model order reduction tool applicable to complex interconnect networks. Different initial representations were considered – circuit models (transfer functions) or frequency domain measurements. The proposed approach uses orthogonal basis functions such as Müntz-Laguerre and Kautz to build an accurate mathematical representation of the original system .A linear operator, related to these functions, is subsequently used to derive a simplified model. The technique is first compared to other approaches using examples available in literature, its full potential being demonstrated on coupled interconnect models.
