Computational investigation of asymmetric coplanar waveguides using neural networks: A microwave engineering exerciseComputational investigation of asymmetric coplanar waveguides using neural networks: A microwave engineering exercise Πλήρης Δημοσίευση σε Συνέδριο Conference Full Paper 2015-10-292005enIn order to compute the characteristic impedance and the relative effective dielectric constant of an asymmetric coplanar waveguide with infinite or finite dielectric thickness, the use of artificial neural networks is valuable. The method of neural computing presented in this paper uses only one neural model for both parameters, for this specific waveguide type. The BFGS quasi-Newton back-propagation algorithm was used to train the developed neural network. Numerical results are given for several configurations along with comparisons with previously published datahttp://creativecommons.org/licenses/by/4.0/243-248International Conference on Engineering EducationProceedings of the 2005 WSEAS International Conference on Engineering Education507-188.pdfChania [Greece]Library of TUC2015-10-29application/pdf303.5 kBfree Liodakis Georgios Λιοδακης Γεωργιος I.O. Vardiambasis K. Karamichalis World Scientific and Engineering Academy and Society Product line engineering, Software software product line engineering product line engineering software