Title :
Initializing artificial neural networks by genetic algorithm to calculate the resonant frequency of single shorting post rectangular patch antenna
Author :
Devi, S. ; Panda, D.C. ; Pattnaik, S.S. ; Khuntia, B. ; Neog, D.K.
Author_Institution :
NERIST, Nirjuli, India
Abstract :
A simple and accurate method for calculating the resonant frequency of a rectangular microstrip patch antenna with a single shorting post by using the artificial neural networks is presented in this paper. Genetic algorithm is used to select the initial weights of artificial neural networks. The calculated resonant frequency is compared with experimental results. The results are in very good agreement with experimental results with decreased computational time.
Keywords :
antenna feeds; antenna theory; backpropagation; computational electromagnetics; genetic algorithms; gradient methods; microstrip antennas; neural nets; artificial neural networks; genetic algorithm; gradient descent backpropagation; initial weights; iteration generation; rectangular microstrip patch antenna; resonant frequency; single shorting post; Artificial neural networks; Backpropagation algorithms; Computer simulation; Educational institutions; Genetic algorithms; Microstrip antennas; Multi-layer neural network; Neural networks; Patch antennas; Resonant frequency;
Conference_Titel :
Antennas and Propagation Society International Symposium, 2003. IEEE
Conference_Location :
Columbus, OH, USA
Print_ISBN :
0-7803-7846-6
DOI :
10.1109/APS.2003.1219810
