In the last few years, intensive research has been done to enhance artificial intelligence (AI)
using optimization techniques. In this paper, we present an extensive review of artificial …

The data-science revolution is poised to transform the way photonic systems are simulated
and designed. Photonic systems are, in many ways, an ideal substrate for machine learning …

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 …

This article introduces the deep neural network method into the field of high-dimensional
microwave modeling. Deep learning is nowadays highly successful in solving complex and …

We review the space-mapping (SM) technique and the SM-based surrogate (modeling)
concept and their applications in engineering design optimization. For the first time, we …

Accurate models of scattering and noise parameters of transistors are instrumental in
facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data …

This paper presents a new technique for artificial neural network (ANN) inverse modeling
and applications to microwave filters. In inverse modeling of a microwave component, the …

Objective functions that appear in engineering practice may come from measurements of
physical systems and, more often, from computer simulations. In many cases, optimization of …

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 paper, we outline the historical evolution of RF and microwave design optimization
and envisage imminent and future challenges that will be addressed by the next generation …