An Adaptive Algorithm for Fully Automated Extraction of Passive Parameterized Macromodels

We present a general framework for the fully automated extraction of stable and passive parameterized macromodels from sampled frequency responses. The proposed iterative algorithm provides an automated selection of the optimal parameter configurations to be simulated by a field solver, based on a combination of data-driven and model-driven metrics. The resulting frequency responses are fitted by a parameterized rational macromodel, whose uniform stability and passivity are enforced. We demonstrate the effectiveness of this framework on a transmission-line network test case.