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Performance parameters prediction of slotted microstrip antennas with modified ground plane using support vector machine

Published online by Cambridge University Press:  28 November 2016

Chandan Roy ,
Taimoor Khan  and
Binod Kumar Kanaujia
Chandan Roy
Affiliation:
Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Cachar, Assam, India
Taimoor Khan*
Affiliation:
Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Cachar, Assam, India
Binod Kumar Kanaujia
Affiliation:
School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India
*
Corresponding author: T. Khan Email: ktaimoor@gmail.com
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Abstract

Artificial neural networks (ANNs) have acquired enormous importance in computing of the performance parameters of microstrip antennas due to their generalized and adaptive features. However, recently the concept of support vector machines (SVMs) has become very much popular in performance parameters computation due to several attractive features over ANNs. Specifically, SVMs outreach ANNs noticeably in terms of execution time. Likewise, ANNs are having multiple local minima problem, whereas a global and unique solution is provided by SVMs. In this paper, several performance parameters like: resonant frequency, gain, directivity, and radiation efficiency of slotted microstrip antennas with modified ground plane are computed with the help of SVM formulation. Comparisons of different parameters of simulated and computed values are illustrated. The achieved radiation patterns at particular resonant frequency in different planes are included as well. A prototype of the optimized antenna is also fabricated and characterized. A good agreement is attained among the computed, simulated, and measured results.

Keywords

SVMMicrostrip antennaSlotted antennaModified ground planeRectangular patchPerformance parametersDifferent slots
Type
Research Papers
Information
International Journal of Microwave and Wireless Technologies , Volume 9 , Issue 5 , June 2017 , pp. 1169 - 1177
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2016 

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