Title :
Analysis and design of microstrip antennas by Artificial Neural Networks
Author :
Santos, Francismari Noronha dos ; Nascimento, Sueli Souza ; Rodriguez-Esquerre, Vitaly F. ; Filho, Fabricio G Simões
Author_Institution :
Dept. of Electr. Eng., Fed. Univ. of Bahia, Salvador, Brazil
fDate :
Oct. 29 2011-Nov. 1 2011
Abstract :
The most common methods of analysis and design of microstrip antennas are the transmission line and the cavity model (analytical), that introduce some simplifications in the mechanisms of radiation from antennas, therefore, some errors are introduced in the determination of its main parameters. On the other hand, numerical methods, which are more accurate, require large computational resources, high processing time and an advanced electromagnetic knowledge. This work deals with the use of Artificial Neural Network (ANN), to represent the relationship between the antenna parameters (frequency, size and dielectric constant) for the analysis and design of several shapes of microstrip antennas.
Keywords :
antenna radiation patterns; electrical engineering computing; microstrip antennas; neural nets; numerical analysis; permittivity; transmission lines; advanced electromagnetic knowledge; antenna parameters; antenna radiation; artificial neural networks; cavity model; computational resources; dielectric constant; high processing time; microstrip antennas; numerical methods; transmission line; Artificial neural networks; Cavity resonators; Microstrip; Microstrip antennas; Neurons; Resonant frequency; Training; Antennas; Microstrip and ANN; Neural Networks;
Conference_Titel :
Microwave & Optoelectronics Conference (IMOC), 2011 SBMO/IEEE MTT-S International
Conference_Location :
Natal
Print_ISBN :
978-1-4577-1662-1
DOI :
10.1109/IMOC.2011.6169358