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Application of Neural Network Model for designing Circular Monopole Antenna

Published on None 2011 by Moumi Pandit, Tanushree Bose
journal_cover_thumbnail

International Symposium on Devices MEMS, Intelligent Systems & Communication
Foundation of Computer Science USA
ISDMISC - Number 2
None 2011
Authors: Moumi Pandit, Tanushree Bose
aad887fa-6387-4bd1-bcf1-cfadb3490401

Moumi Pandit, Tanushree Bose . Application of Neural Network Model for designing Circular Monopole Antenna. International Symposium on Devices MEMS, Intelligent Systems & Communication. ISDMISC, 2 (None 2011), 18-21.

@article{
author = { Moumi Pandit, Tanushree Bose },
title = { Application of Neural Network Model for designing Circular Monopole Antenna },
journal = { International Symposium on Devices MEMS, Intelligent Systems & Communication },
issue_date = { None 2011 },
volume = { ISDMISC },
number = { 2 },
month = { None },
year = { 2011 },
issn = 0975-8887,
pages = { 18-21 },
numpages = 4,
url = { /proceedings/isdmisc/number2/3450-isdm033/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Symposium on Devices MEMS, Intelligent Systems & Communication
%A Moumi Pandit
%A Tanushree Bose
%T Application of Neural Network Model for designing Circular Monopole Antenna
%J International Symposium on Devices MEMS, Intelligent Systems & Communication
%@ 0975-8887
%V ISDMISC
%N 2
%P 18-21
%D 2011
%I International Journal of Computer Applications
Abstract

In this paper, Neural network model has been used to estimate the feedgap which is one of the design parameters of circular monopole antenna (CMA) required to make it operate in a particular frequency band. A Neural Network (NN) model is prepared using Feed Forward Back Propagation Algorithm which can be further used for designing a CMA operating between 2GHz and 12 GHz. The results obtained by the NN model are compared with the results of IE3D software which shows good agreement between the two. The model is accurate enough to measure the feedgap parameter of the monopole antenna which can be used to design the antenna. Thus this model eliminates the long time consuming process of finding the value of feedgap parameter using costly software packages.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Back Propagation Algorithm Neural Network Circular Monopole Antenna