Modeling of microwave pyramidal absorbers using artificial neural networks

In this paper, a possibility of employing artificial neural networks in evaluation of microwave pyramidal absorbers´ performance is presented. The developed neural model predicts reflection coefficient of the absorber at different incident angles and operating frequencies, for horizontally polarized EM wave. Efficiency and simplicity of determining the reflection coefficient present main advantage of the proposed neural model in regard to complex electromagnetic models.