Premium
Determination of complex permittivity with neural networks and FDTD modeling
Author(s) -
Eves E. Eugene,
Kopyt Paweł,
Yakovlev Vadim V.
Publication year - 2003
Publication title -
microwave and optical technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.304
H-Index - 76
eISSN - 1098-2760
pISSN - 0895-2477
DOI - 10.1002/mop.11323
Subject(s) - finite difference time domain method , permittivity , microwave , dielectric , artificial neural network , dielectric permittivity , reflection coefficient , reflection (computer programming) , materials science , relative permittivity , simple (philosophy) , optics , matching (statistics) , acoustics , electronic engineering , computer science , computational physics , optoelectronics , mathematics , physics , engineering , telecommunications , artificial intelligence , statistics , philosophy , epistemology , programming language
A simple novel cavity‐independent method of determination of dielectric properties of arbitrarily shaped materials is presented. Complex permittivity is reconstructed using a neural networking procedure matching the measured and FDTD‐modeled frequency characteristics of the reflection coefficient. High accuracy and practical suitability are demonstrated through numerical testing and determination of dielectric properties of fresh and saline water at 915 MHz. © 2004 Wiley Periodicals, Inc. Microwave Opt Technol Lett 40: 183–188, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.11323