Advanced Neural Space Mapping-Based Inverse Modeling Method for Microwave Filter Design

Abstract

This letter proposes an advanced neural space mapping (NSM)-based inverse modeling method and its applications to microwave filter design. For the first time, the NSM method is introduced into inverse microwave modeling with input dimensional reduction (IDR). By using the Fourier transform and its low-frequency subspaces, we convert the S-parameter curve into a signal spectrum where the energy is concentrated in the low-frequency range, to reduce the dimension of the inverse model. We also propose a two-stage training algorithm for the NSM-based inverse model, along with its application methodology for microwave filter design. Two microwave filter design examples are presented to demonstrate the feasibility of the proposed method.