Modeling of Microstrip Lines Using Neural Networks: Applications to the Design and Analysis of Distributed Microstrip Circuits

In this article, two models for solving microstrip lines are presented. The models utilize radial-basis-function neural networks. Using the first model, one estimates the effective dielectric constant and the width of the microstrip line, knowing its characteristic impedance and the frequency. The second model provides the effective dielectric constant and the characteristic impedance of the line based on knowledge of its width and the frequency. Besides their remarkably fast responses, the proposed models are capable of estimating the required quantities with very high accuracy. The potential of the proposed models is demonstrated in the design and analysis of two distributed microstrip circuits.