Advances in hybrid format‐based neuro‐transfer function techniques for parametric modeling of microwave components - Ma, Li; Zhang, Qi‐Jun; Liu, Wei; Zhang, Jianan (International journal of numerical modelling, 2024)
Electromagnetic (EM) parametric modeling has become significant for EM designs of microwave devices. This paper outlines recent advances in hybrid format‐based neuro‐transfer function (TF) techniques for EM parametric modeling of microwave devices. To solve the problem of high‐sensitivity, a novel decomposition approach is discussed to develop a rational‐based neuro‐TF model of EM behavior of microwave devices. To handle the issue of non‐smoothness and discontinuity, a parametric modeling technique incorporating pole‐residue/rational and neural network hybrid transfer function (short for rational/pole‐residue hybrid neuro‐TF) of EM behavior is reviewed. This technique effectively combines rational and residue‐pole formats of the transfer functions. Compared with the residue‐pole‐based neuro‐TF modeling approach and the rational‐based neuro‐TF modeling approach, the rational/pole‐residue hybrid neuro‐TF technique allows for better accuracy in large geometrical changes and high order applications. A parametric modeling method combining neural network and polynomial‐transfer function (neuro‐PTF) is further presented as an advanced version of the rational/pole‐residue hybrid neuro‐TF method. In this approach, the pole–residue‐based transfer function and the polynomial function are used together to describe the EM responses, and can produce more accurate models, especially with large geometrical variables. Following the modeling process, trained models can be used to provide fast and accurate EM response predictions and can subsequently be used for advanced circuit and system design.