Innovative approaches and tools play an important role in shaping design, characterization
and optimization for the field of photonics. As a subset of machine learning that learns …

Deep neural networks (DNNs) are empirically derived systems that have transformed
traditional research methods, and are driving scientific discovery. Artificial electromagnetic …

Abstract Machine learning (ML), as a component of artificial intelligence, encourages
structural design exploration which leads to new technological advancements. By …

Defected ground structures (DGS) have been developed to improve characteristics of many
microwave devices. Although the DGS has advantages in the area of the microwave filter …

Neural networks found significant applications in microwave CAD. In this paper, after
providing a brief description of neural networks employed so far in this context, we illustrate …

An artificial neural network (ANN) has been developed and tested for square-patch antenna
design. It transforms the data containing the dielectric constant (/spl epsiv//sub r/), thickness …

Artificial neural networks (ANN) recently gained attention as a fast and flexible vehicle to
microwave modeling and design. Fast neural models trained from measured/simulated …

We present a neural network approach to the problem of finding the weights of one-(1-D)
and two-dimensional (2-D) adaptive arrays. In modern cellular satellite mobile …

Many applications of microstrip antenna are rendered by their inherent narrow bandwidth. In
this paper a new approach is proposed to design inset feed microstrip antenna with slots in it …

In the last two decades, artificial neural network (ANN) technology has leaped forward and is
now being applied in different areas such as speech recognition, control …