Application of Artificial Neural Networks for Modeling of the Frequency-Dependent Performance of Surface Acoustic Wave Resonators

Abstract

This paper deals with the application of the artificial neural networks (ANNs) for modeling the performance of four commercial two-port surface acoustic wave (SAW) resonators. ANNs are used to reproduce the frequency-dependent behaviour of the short-circuit input admittance, thereby enabling a fast and accurate estimation of the resonant parameters.