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Development and Validation of an ANN-Based Approach for Temperature-Dependent Equivalent Circuit Modeling of SAW Resonators

Authors :
Miloš Radojković
Giovanni Gugliandolo
Mariangela Latino
Zlatica Marinković
Giovanni Crupi
Nicola Donato
Source :
Micromachines, Vol 14, Iss 5, p 967 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

In this paper, a novel approach is proposed for modeling the temperature-dependent behavior of a surface acoustic wave (SAW) resonator, by using a combination of a lumped-element equivalent circuit model and artificial neural networks (ANNs). More specifically, the temperature dependence of the equivalent circuit parameters/elements (ECPs) is modeled using ANNs, making the equivalent circuit model temperature-dependent. The developed model is validated by using scattering parameter measurements performed on a SAW device with a nominal resonant frequency of 423.22 MHz and under different temperature conditions (i.e., from 0 °C to 100 °C). The extracted ANN-based model can be used for simulation of the SAW resonator RF characteristics in the considered temperature range without the need for further measurements or equivalent circuit extraction procedures. The accuracy of the developed ANN-based model is comparable to that of the original equivalent circuit model.

Details

Language :
English
ISSN :
2072666X
Volume :
14
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Micromachines
Publication Type :
Academic Journal
Accession number :
edsdoj.1d45b92890da4f7ca5552079acd8f203
Document Type :
article
Full Text :
https://doi.org/10.3390/mi14050967