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Modeling and design of printed antennas using neural networks
Author(s) -
Tighilt Yamina,
Bouttout Farid,
Khellaf Abdelhafid
Publication year - 2011
Publication title -
international journal of rf and microwave computer‐aided engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.335
H-Index - 39
eISSN - 1099-047X
pISSN - 1096-4290
DOI - 10.1002/mmce.20509
Subject(s) - microwave , antenna (radio) , planar , substrate (aquarium) , patch antenna , microstrip antenna , artificial neural network , acoustics , electronic engineering , function (biology) , engineering , computer science , electrical engineering , telecommunications , physics , geology , oceanography , computer graphics (images) , machine learning , evolutionary biology , biology
A single neural network is developed to model the resonant frequency of rectangular patch printed on uniaxially anisotropic substrate with air gap using effective parameters in conjunction with spectral dyadic Green's function. Also, the strength of ANN models in antenna design is demonstrated by considering two case studies: the design of circular patch antenna and planar inverted‐F antenna. Results show good agreement with literature. © 2011 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2011.