Sulayman Joof, Cemanur Aydinalp, Mehmet Nuri Akinci, Tuba Yilmaz, Ibrahim Akduman.
In recent years, neural networks and deep learning algorithms have been employed to solve microwave related problems. These algorithms generally require a large amount of data to design a robust model which can be costly and time consuming. In this presentation, our proposed fast and cost-effective technique to obtain the reflection coefficients of a material under test with the open-ended coaxial probe will be presented. This method can be implemented to generate synthetic reflection coefficients dataset which is close enough to real measured data. Additionally, the generated dataset from this method was used to design a deep learning model to retrieve the complex dielectric properties of some standard liquids and mixtures.
