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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/8219
Title: Design of custom-made stacked patch antennas: A machine learning approach
Authors: Jain S.K.
Patnaik, Amalendu
Sinha S.N.
Published in: International Journal of Machine Learning and Cybernetics
Abstract: Machine learning approaches, viz. particle swarm optimization in conjunction with neural networks have been used to develop a user friendly tool to design custom-made stacked patch antennas in the entire X-Ku band for satellite communication application. The role of the neural network is to develop a black-box model to relate the frequencies of operation of the antenna with its dimensional parameters. This trained neural network was embedded in the loop of a particle swarm optimizer to decide the design dimensions required for specific user defined frequencies. The effectiveness and accuracy of the developed model are verified by simulations and experimental measurements. © 2012 Springer-Verlag.
Citation: International Journal of Machine Learning and Cybernetics (2013), 4(3): 189-194
URI: https://doi.org/10.1007/s13042-012-0084-x
http://repository.iitr.ac.in/handle/123456789/8219
Issue Date: 2013
Keywords: Neural network
Particle swarm optimization
Stacked patch antenna
ISSN: 18688071
Author Scopus IDs: 55461296100
7102813204
7403739821
Author Affiliations: Jain, S.K., Department of Electronics and Computer Engineering, Indian Institute of Technology Roorkee, Roorkee, 247 667, India
Patnaik, A., Department of Electronics and Computer Engineering, Indian Institute of Technology Roorkee, Roorkee, 247 667, India
Sinha, S.N., Department of Electronics and Computer Engineering, Indian Institute of Technology Roorkee, Roorkee, 247 667, India
Corresponding Author: Patnaik, A.; Department of Electronics and Computer Engineering, Indian Institute of Technology Roorkee, Roorkee, 247 667, India; email: apatnaik@ieee.org
Appears in Collections:Journal Publications [ECE]

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