Magneto-Dielectric Composites Characterization Using Resonant Sensor and Neural Network Modeling

被引:1
|
作者
Alvarez-Botero, German [1 ]
Lobato-Morales, Humberto [2 ]
Hui, Katherine [3 ]
Tarabay, Naji [3 ]
Sanchez-Vargas, Jeu [2 ]
Velez, Camilo [3 ]
Mendez-Jeronimo, Gabriela [2 ]
机构
[1] Univ Publ Navarra, Dept Elect Elect & Commun Engn, Pamplona 31006, Spain
[2] CICESE, Ensenada 22860, Mexico
[3] Univ Calif Irvine, Mech & Aerosp Engn Dept, Magnet Microsyst & Microrobot Lab, Irvine, CA 92697 USA
来源
关键词
Artificial neural networks (ANNs); microwavecharacterization; PDMS-Fe3O4; composite; PERMITTIVITY; PERMEABILITY; ANTENNA; DESIGN;
D O I
10.1109/LMWT.2024.3356418
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This article presents a novel way to estimate magnetodielectric composites' complex permittivity (epsilon) and per-meability (mu). A methodology based on artificial neural network(ANN) modeling is proposed to determine epsilon and mu fromS-parameter measurements around 2.45 GHz, obtained using a new microstrip split ring resonator (SRR)-based resonant sensor
引用
收藏
页码:447 / 450
页数:4
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