Title :
Neural model for conventional coplanar waveguide sandwiched between two dielectric substrates
Author :
Mustafa, Turkmen ; Celal, Yildiz ; Seref, Sagiroglu
Author_Institution :
Dept. of Electron. Eng., Erciyes Univ., Kayseri, Turkey
Abstract :
In this work a new approach based on artificial neural networks (ANNs) was successfully introduced to determine the characteristic parameters of conventional coplanar waveguides (CPWs) and CPW sandwiched between two dielectric substrates. Only one neural model was used to calculate the characteristic parameters of conventional CPWs and sandwiched CPWs. This neural model was trained with extended delta-bar-delta (EDBD). The characteristic parameters obtained from neural model are in very good agreement with theoretical and experimental results available in the literature. The neural model presented in this work is not time consuming and easily included in CAD systems.
Keywords :
coplanar waveguides; dielectric materials; electric impedance; neural nets; permittivity; artificial neural networks; characteristic impedance; characteristic parameters; dielectric substrates; effective relative permittivity; extended delta-bar-delta; neural model; sandwiched conventional coplanar waveguides; Artificial neural networks; Coplanar waveguides; Dielectric substrates; Electronic mail; Impedance; Integral equations; Microstrip antennas; Microwave integrated circuits; Permittivity; Power transmission lines;
Conference_Titel :
Electromagnetic Compatibility, 2003. EMC '03. 2003 IEEE International Symposium on
Print_ISBN :
0-7803-7779-6
DOI :
10.1109/ICSMC2.2003.1428249