Álvarez Botero, Germán AndrésLobato-Morales, HumbertoHui, KatherineTarabay, NajiSánchez-Vargas, JeuVélez, CamiloMéndez-Jerónimo, Gabriela2024-06-052024-06-052024Álvarez-Botero, G., Lobato-Morales, H., Hui, K., Tarabay, N., Sanchez-Vargas, J., Velez, C., Méndez-Jerónimo, G. (2024) Magneto-dielectric composites characterization using resonant sensor and neural network modeling. IEEE Microwave and Wireless Components Letters, 34(4), 447-450. https://doi.org/10.1109/LMWT.2024.3356418.1531-130910.1109/LMWT.2024.3356418https://academica-e.unavarra.es/handle/2454/48258This article presents a novel way to estimate magnetodielectric composites’ complex permittivity (ε) and permeability (µ). A methodology based on artificial neural network (ANN) modeling is proposed to determine ε and µ from S-parameter measurements around 2.45 GHz, obtained using a new microstrip split ring resonator (SRR)-based resonant sensor.application/pdfeng© 2024 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License.Artificial neural networks (ANNs)Microwave characterizationPDMS-Fe3O4 compositeinfo:eu-repo/semantics/article2024-06-05info:eu-repo/semantics/openAccess