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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/8447
Title: Modeling frequency reconfigurable antenna array using neural networks
Authors: Patnaik, Amalendu
Anagnostou D.
Christodoulou C.G.
Lyke J.C.
Published in: Microwave and Optical Technology Letters
Abstract: In order to avoid the computational complexities involved in analyzing reconfigurable antennas, neural networks are used as an alternate approach. The neural network finds the location of the operational frequency hands for any combination of switches connecting different radiating elements. The network outputs are compared with the experimentally measured results. © 2005 Wiley Periodicals, Inc.
Citation: Microwave and Optical Technology Letters (2005), 44(4): 351-354
URI: https://doi.org/10.1002/mop.20632
http://repository.iitr.ac.in/handle/123456789/8447
Issue Date: 2005
Keywords: Antenna array
MEMS
Neural networks
Reconfigurable antennas
ISSN: 8952477
Author Scopus IDs: 7102813204
6701668156
35465847700
57205900168
Author Affiliations: Patnaik, A., Department of Electrical Engineering, University of New Mexico, Albuquerque, NM 87131, United States
Anagnostou, D., Department of Electrical Engineering, University of New Mexico, Albuquerque, NM 87131, United States
Christodoulou, C.G., Department of Electrical Engineering, University of New Mexico, Albuquerque, NM 87131, United States
Lyke, J.C., Air Force Research Laboratory, VSSE Kirtland AFB, Albuquerque, NM, United States
Corresponding Author: Patnaik, A.; Department of Electrical Engineering, University of New Mexico, Albuquerque, NM 87131, United States
Appears in Collections:Journal Publications [ECE]

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