Design of miniaturized FSS structure using Optimization Technique based on Machine Learning

This work presents the design of a miniaturized FSS structure characterized by three resonant frequencies for S and C-band applications. When an incident normalized plane wave is illuminated, the miniaturized FSS shows three rejecting bands at 2.42 GHz, 7.2 GHz, and 9 GHz simultaneously with the wide bandwidth of 2.3 GHz from 5.8 GHz to 8.1 GHz. The Frequency Selective Surface is designed by creating some rectangular slots within the square patch. The resultant slotted square patch can achieve a size reduction of 93.2%, 47.8%, and 18.98%. The measured results show great acceptance for the simulated ones. The theoretical investigation has been done by the Ansoft HFSS EM simulation tool. An experimental investigation has been performed and analytical results are achieved. A machine learning technique is implemented which also validates the experimental resonant frequency values.