Neural space mapping optimization for EM-based design of RF and microwave circuits

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Space-mapping-based interpolation for engineering optimization (2006, background): “…such as implicit space mapping [3], [9] and output space mapping [4]; 2) development of new SM-based models [10], [11]; 3) theoretical justification of space mapping and convergence theory for SM optimization algorithms [12], neuro-SM [13]–[17], and applications of SM (e.g., [18] and [19]).”
EM-based optimization of microwave circuits using artificial neural networks: the state-of-the-art (2003, methodology): “To illustrate how the difference between the fine and coarse model responses can be as complex as the fine model responses themselves, consider the high-temperature superconducting (HTS) microstrip filter in [33].”
Space mapping: the state of the art (2004, methodology): “After updating an ANN-based surrogate [15], a fine model optimal design is predicted in NSM [16] by (re)optimizing the surrogate.”