Machine learning (ML) has demonstrated significant potential in accelerating the design of
microwave components owing to its great ability to approximate the projection between …

Electromagnetic (EM) structures play a significant role in wireless communication, radar
detection, medical imaging, and so on. Machine learning (ML) has been increasingly …

One challenge in the design of frequency selective surface (FSS) is that the designed results
are difficult to meet the accuracy demand of various physical properties simultaneously, part …

Deep-learning-assisted antenna design methods such as surrogate models have gained
significant popularity in recent years due to their potential to greatly increase design …

Deep learning (DL) plays a vital role in the design of electromagnetic (EM) structures.
However, in current research, a single neural network typically supports only one structure …

To deal with different beamforming network (BFN) design tasks, a generalized auto-design
methodology is developed by the following three steps. First, a structure reconfiguration is …

A dual-band dual-polarization frequency selective surface (FSS) with wide-range flexible
band ratio and wide angular stability is proposed. Subwavelength metal walls acted as plate …

In this letter, we propose an inverse design framework of electromagnetic metasurfaces
(EMMS) realized by optimizing latent variables in a separated latent space. In the training …

This study proposes an inverse design framework for metasurfaces based on a neural
network capable of generating infinite and continuous latent representations to fully span the …

In modern wireless telecommunication systems, antenna arrays are widely used as
elements of multiple–input multiple–output technology. In the fifth-generation systems …