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Artificial Neural Network Model for Suspended Shorted Rectangular Microstrip Antennas

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IJCA Proceedings on International Conference on Computer Technology
© 2015 by IJCA Journal
ICCT 2015 - Number 2
Year of Publication: 2015
Authors:
Amit A. Deshmukh
Shivali D. Kulkarni
Venkata A. P. C

Amit A Deshmukh, Shivali D Kulkarni and Venkata A.p.c. Article: Artificial Neural Network Model for Suspended Shorted Rectangular Microstrip Antennas. IJCA Proceedings on International Conference on Computer Technology ICCT 2015(2):6-10, September 2015. Full text available. BibTeX

@article{key:article,
	author = {Amit A. Deshmukh and Shivali D. Kulkarni and Venkata A.p.c},
	title = {Article: Artificial Neural Network Model for Suspended Shorted Rectangular Microstrip Antennas},
	journal = {IJCA Proceedings on International Conference on Computer Technology},
	year = {2015},
	volume = {ICCT 2015},
	number = {2},
	pages = {6-10},
	month = {September},
	note = {Full text available}
}

Abstract

The bandwidth in half wave or quarter wave length microstrip antennas is increased by using suspended configuration in which the radiating patch is suspended above the ground plane of finite air gap. While using thicker substrate, a closed form expressions for calculating edge extension length due to the fringing fields in shorted patch, is not available. In this paper, an artificial neural network model to calculate the shorted patch length and edge extension length for air suspended shorted rectangular microstrip antenna over wide frequency range (500 to 6000 MHz) and on thicker air substrate (0. 04?0 to 0. 1?0) is proposed. The resonance frequency calculated by using proposed neural network model closely agrees with the simulated and measured results. Thus, proposed model can be used to accurately calculate shorted patch length for shorted rectangular microstrip antenna.

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