Quasi-static Models Based on Artificial Neural Networks for Calculating the Characteristic Parameters of Multilayer Cylindrical Coplanar Waveguide and Strip Line

In this paper, two different neural models are proposed for calculating the quasi-static parameters of multilayer cylindrical coplanar waveguides and strip lines. These models were basically developed by training the artificial neural networks with the numerical results of quasi-static analysis. Neural models were trained with four different learning algorithms to obtain better performance and faster convergence with simpler structure. When the performances of neural models are compared with each other, the best test results are obtained from the multilayered perceptrons trained by the LevenbergMarquardt algorithm. The results obtained from the neural models are in very good agreements with the theoretical results available in the literature.