Title :
Analysis of EBG structures implemented on CPW components by using EM-ANN models
Author :
Gao, Chu ; Wang, Yunyi
Author_Institution :
Radio Eng. Dept., Southeast Univ., Nanjing, China
Abstract :
An efficient electromagnetically trained artificial neural-network (EM-ANN) is proposed to calculate S parameters of electromagnetic band-gap (EBG) circuits for coplanar waveguide (CPW) components. An EBG band-stop filter and an EBG resonator are studied. The results are compared with experiment results. The agreement shows that this method is very effective for analyzing these types of circuits. We conclude that using EM-ANN models in the analysis of EBG structures implemented on CPWs is effective and yields S parameters with sufficient accuracy. Moreover, it is efficient; only several seconds are needed instead of time-consuming momentum simulations. Our method is a practical one and can be used in future CAD.
Keywords :
S-parameters; band-stop filters; computational electromagnetics; coplanar waveguide components; learning (artificial intelligence); neural nets; photonic band gap; resonators; waveguide filters; CPW components; EBG structures; S parameters; band-stop filter; coplanar waveguide components; electromagnetic band-gap circuits; electromagnetically trained artificial neural-network; resonator; Circuits; Coplanar waveguides; Design automation; Electromagnetic modeling; Electromagnetic waveguides; Metamaterials; Periodic structures; Resonator filters; Transmission line matrix methods; Vectors;
Conference_Titel :
Antennas and Propagation Society International Symposium, 2002. IEEE
Print_ISBN :
0-7803-7330-8
DOI :
10.1109/APS.2002.1016999
