A review of artificial neural networks applications in microwave computer-aided design (invited article)

Abstract

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 some of their most significant applications and typical issues arising in practical implementation. We also summarize current research tendencies and introduce use of self‐organizing maps enhancing model accuracy and applicability. We conclude considering some future developments and exciting perspectives opened from use of neural networks in microwave CAD. ©1999 John Wiley & Sons, Inc. Int J RF and Microwave CAE 9: 158–174, 1999.

A Microstrip Antenna Shape Grammar

“…Not surprisingly the GA has been applied to the control of reconfigurable antennas. In (D. S. Linden,2002) and (Zhang Min et al,2004), the GA is applied to tune the antenna for maximum signal strength on-situ and in (Coleman,C.M. et al,2000) and (L. N. Pringle et al,2004) the GA is used to tune the antenna over a large range of frequencies.…”

Response surface space mapping for electromagnetic optimization

“…The role of this mapping is to transform the fine input parameters so that in step 8 behaves like the fine model. The mapping is implemented using an artificial neural network (ANN) [8]. The RSSM algorithm essentially builds and enhances the mapped coarse model until a desirable optimum is achieved.…”

Response clustering for electromagnetic modeling and optimization

“…According to the universal approximation theorem, there always exists a three-layer perceptron ANN that can approximate any arbitrary nonlinear continuous multidimensional function to any desired accuracy [3]. The three-layer perceptron, having an input layer , a hidden layer , and an output layer , is used throughout this study.…”