微波谐振器在湿度检测中的应用:人工神经网络与洛伦兹拟合的比较分析

G. Gugliandolo, Z. Marinković, G. Campobello, G. Crupi, N. Donato
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引用次数: 1

摘要

本文将人工神经网络(ann)与Lorentzian拟合方法应用于湿度传感器的谐振特性建模,并进行了对比研究。被测器件(DUT)是一个微波微带谐振器,在FR4衬底上开发,在间隙上沉积Ag@a-Fe2O3纳米结构层,旨在湿度传感应用。为了确定被测设备的频率依赖行为,反射系数(Γ)从3.4 GHz测量到5.6 GHz。根据给定的应用程序需求,每种分析的方法都有优点和缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Microwave Resonator for Humidity Detection Applications: A Comparative Analysis between ANNs and Lorentzian Fitting Method
This work focuses on a comparative study between the artificial neural networks (ANNs) and the Lorentzian fitting method, which are applied for modeling of the resonant characteristics of a humidity sensor. The device under test (DUT) is a microwave microstrip resonator, developed on FR4 substrate, with a Ag@a-Fe2O3 nanostructured layer deposited on the gap, aimed at humidity sensing applications. To determine the frequency-dependent behavior of the tested device, the reflection coefficient (Γ) is measured from 3.4 GHz up to 5.6 GHz. It is achieved that each analyzed approach has pros and cons, depending on the given application requirements.
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