This paper presents a Neural Network model for the
design of Micro-strip Antenna for Ultra wideband (UWB)
applications which can be operated in a desired frequency range
between 2 GHz to 20 GHz. Artificial neural network based on
back -propagation (BP) and radial basis network (RBN)
algorithms have been used in designing rectangular patch
antenna highlighting the difference between them and the results
extracted from these methods are then matched with the results
obtained by Computer Simulation Technology (CST) simulation
software and are found to be in good agreement. These two
algorithms prove to be very advantageous as they can be used to
design any rectangular patch monopole antenna of a particular
resonant frequency and bandwidth without any lengthy iterative
processes.
MOUMI PANDIT : received her B.Tech degree in Electrical
engineering from the West Bengal University of Technology,
India in 2008, and the M.Tech degree in electrical and electronics
engineering with specialization in Power Electronics from Sikkim
Manipal University, India in 2011.Presently she is pursuing PhD
in electronic and communication engineering. Since 2009 she
has been working as Assistant Professor in department of
electrical and electronics engineering in Sikkim Manipal Institute
of Technology. Her research interest include power electronics,
neural network, antenna and optimization techniques using
artificial intelligence.
Dr. TANUSHREE BOSE ROY : Born in 1979, she received her
B.Sc (electronics) and M.Sc (Electronics and
Telecommunication) degree in the year 2000 and 2002
respectively from Birla Institute of Technology, Mesra. In the year
2011, she was awarded her Ph.D degree in “ Development of
some Printed Antenna Using Neural Network” from the same
Institute. She has also served as a faculty member in University
Polytechnic which is a constituent part of B.I.T., Mesra, from the
year 2003 to 2008. She then joined Sikkim Manipal Institute of
Technology, in the year 2008 as faculty member and is serving
the same organization till date.
Her research interest is in the field of Modern Antennas, Artificial
Neural Network and Wireless Communication.
Microstrip Antenna
backpropagation method
radial basis method
neural network
The networks that were trained give all the design
parameters of the monopole antenna for any desired
resonant frequency. So they are very useful. After proper
training, they completely bypass repeated use of complex
iterative processes for new design presented to it.
Fabrication of this type of antenna can easily be done
using a single metal plate, resulting into a low
construction cost [10]. Impedance bandwidth of very
wide of about 20GHz (2GHz-20GHz) has been obtained
with this antenna. Out of the two models, the BP model is
much better than the RBF model as it reduces the error
performance.
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Feb.1998.
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[8] En.m.wikipedia.org/wiki/Artificial_intelliengence
[9] Moumi Pandit and Tanushree Bose, “Artificial
Models for Determining Antenna Parameters for a
Resonant Frequency” International Journal of
Current Engineering and Technology, Vol.3,No.2 ,
2013,pp.297-302.
[10] Kin-Lu Wong, Senior Member, IEEE, Chih-Hsien
Wu, and Saou-Wen (Stephen) Su.“Ultrawide-Band Square Planar Metal-Plate Monopole Antenna With
a Trident-Shaped Feeding Strip,” IEEE Transactions
on Antennas and Propagation, Vol. 53, No.4, 2005
