This article presents an overview of artificial neural network (ANN) techniques for a
microwave computer-aided design (CAD). ANN-based techniques are becoming useful for …

Environmental sensors have come a long way over the last decade, surged in variety and
capabilities. Such growth was impossible without developing wireless technologies …

A multistage collaborative machine learning (MS-CoML) method that can be applied to
efficient multiobjective antenna modeling and optimization is proposed. Machine learning …

This paper proposes an advanced technique to develop combined neural network and pole-
residue-based transfer function models for parametric modeling of electromagnetic (EM) …

In this communication, a novel artificial neural network (ANN) model is proposed to describe
the antenna performance with various parameters. In this model, three parallel and …

With the rapid development of modern wireless communications and radar, antennas and
arrays are becoming more complex, therein having, eg, more degrees of design freedom …

Artificial neural networks (ANNs) are information processing systems, with their design
inspired by studies of the ability of the human brain to learn from observations and …

We develop a deep neural network (DNN) modeling methodology to predict the radiated
emissions of a shielding enclosure in terms of its aperture attributes including aperture …

This paper proposes a pole-residue-based adjoint neuro-transfer function (neuro-TF)
technique with electromagnetic (EM) sensitivity analysis for parametric modeling of EM …

Space mapping is a recognized surrogate-based optimization method to accelerate the
electromagnetic (EM) design. In this article, for the first time, space mapping is elevated from …