人工神经网络在表面声波谐振器频率特性建模中的应用

2021 56th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST) Pub Date : 2021-06-16 DOI:10.1109/ICEST52640.2021.9483548

Z. Marinković, G. Gugliandolo, G. Campobello, G. Crupi, N. Donato

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引用次数: 6

摘要

本文讨论了人工神经网络(ann)在四个商用双端口表面声波(SAW)谐振器性能建模中的应用。人工神经网络用于再现短路输入导纳的频率依赖行为，从而能够快速准确地估计谐振参数。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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.

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来源期刊

2021 56th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST)

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