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Download fileMicrowave Dielectric Property Retrieval from Open-Ended Coaxial Probe Response with Deep Learning
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posted on 12.11.2021, 22:42 by Cemanur Aydinalp, Sulayman Joof, Mehmet Nuri Akinci, Ibrahim Akduman, Tuba YilmazTuba YilmazIn the manuscript, we propose a new technique for determination of Debye
parameters, representing the dielectric properties of materials, from the reflection coefficient response
of open-ended coaxial probes. The
method retrieves the Debye parameters using a deep learning model designed
through utilization of numerically generated data. Unlike real data, using synthetically generated input and
output data for training purposes provides representation of a wide variety of materials with rapid data generation. Furthermore, the
proposed method provides design flexibility and can be applied to any desired
probe with intended dimensions and material. Next, we experimentally verified the designed deep
learning model using measured reflection coefficients when the probe was
terminated with five different standard liquids, four mixtures,and a gel-like
material.and compared the results with the literature. Obtained mean percent relative
error was ranging from 1.21±0.06 to 10.89±0.08. Our work also presents a large-scale
statistical verification of the proposed dielectric property retrieval technique.