• DocumentCode
    1579120
  • Title

    A Heuristic Artificial Neural Network Design of Resonant Frequency of Rectangular Microstrip/Patch Antennas

  • Author

    Moghaddasi, Mohammad Nasar ; Barjoei, Pouya Derakhshan

  • Author_Institution
    Member of Central Comm. for Sci., Literacy & Art Soc., Islamic Azad Univ., Tehran
  • fYear
    2008
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In this paper, both the synthesis and analysis of rectangular microstrip antenna models based on the artificial neural networks are presented to calculate accurately the resonant frequency of the rectangular microstrip antennas. Artificial neural networks are developed from neurophysiology by morphologically and computationally mimicking human brains The resonant frequency results obtained by using rectangular microstrip antenna characteristics and neural network models are very good agreement with the experimental results available in the literature, this paper presents a multilayer perceptron (MLP)modular neural network, training with the resilient back propagation algorithm which has been used for nonlinear device modeling in microwave band.
  • Keywords
    backpropagation; microstrip antennas; multilayer perceptrons; neural nets; back propagation algorithm; heuristic artificial neural network design; human brain; multilayer perceptron modular neural network; neurophysiology; nonlinear device modeling; patch antenna; rectangular microstrip antenna; resonant frequency; Artificial neural networks; Biological neural networks; Brain modeling; Microstrip antennas; Multi-layer neural network; Network synthesis; Neural networks; Neurophysiology; Patch antennas; Resonant frequency; Neural network; Perceptron; Rectangular patch antenna; Resonant frequency;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Communication Technologies: From Theory to Applications, 2008. ICTTA 2008. 3rd International Conference on
  • Conference_Location
    Damascus
  • Print_ISBN
    978-1-4244-1751-3
  • Electronic_ISBN
    978-1-4244-1752-0
  • Type

    conf

  • DOI
    10.1109/ICTTA.2008.4530138
  • Filename
    4530138