Neural models for the broadside-coupled V-shaped microshield coplanar waveguides


Guney K. , Yidiz C. , Kaya S., Turkmen M.

International Journal of Infrared and Millimeter Waves, vol.27, no.9, pp.1241-1255, 2006 (Journal Indexed in SCI Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 27 Issue: 9
  • Publication Date: 2006
  • Doi Number: 10.1007/s10762-006-9132-5
  • Title of Journal : International Journal of Infrared and Millimeter Waves
  • Page Numbers: pp.1241-1255

Abstract

This article presents a new approach based on multilayered perceptron neural networks (MLPNNs) to calculate the odd-and even-mode characteristic impedances and effective permittivities of the broadside-coupled V-shaped microshield coplanar waveguides (BC-VSMCPWs). Six learning algorithms, bayesian regulation (BR), Levenberg-Marquardt (LM), quasi-Newton (QN), scaled conjugate gradient (SCG), resilient propagation (RP), and conjugate gradient of Fletcher-Powell (CGF), are used to train the MLPNNs. The neural results are in very good agreement with the results reported elsewhere. When the performances of neural models are compared with each other, the best and worst results are obtained from the MLPNNs trained by the BR and CGF algorithms, respectively. © Springer Science+Business Media, LLC 2006.