This topic focuses on the design and analysis of Frequency Selective Surfaces (FSS) for
electromagnetic interference (EMI) shielding and filtering applications. FSS structures are designed
to selectively transmit or block specific frequency bands, thereby reducing unwanted
electromagnetic radiation. Deep Neural Networks (DNNs) are employed to model the relationship
between FSS design parameters—such as geometry, dimensions, substrate properties, and
operating frequency—and their electromagnetic response. The developed DNN model can enable
rapid prediction and optimization of FSS performance, reducing the need for repeated
computationally intensive electromagnetic simulations. The study aims to develop efficient,
accurate, and optimized FSS designs suitable for advanced EMI control and electromagnetic
compatibility applications.