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dc.contributor.authorSinghal, Rahul-
dc.date.accessioned2023-03-07T04:37:34Z-
dc.date.available2023-03-07T04:37:34Z-
dc.date.issued2021-10-
dc.identifier.urihttps://link.springer.com/article/10.1007/s11277-021-09220-6-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9541-
dc.description.abstractIn this paper, a flexible and a modular approach to design complementary split-ring resonator (CSRR) metamaterials is presented which is further applied for a planar antenna miniaturization. The design task is treated as an optimization problem and one of the well-known computational techniques, particle swarm optimization (PSO) is employed to identify the design dimensions of planar CSRR structure followed by a C-band antenna miniaturization. Two trained neural networks (NNs) make use of machine learning (ML) approach to reduce the design time. The proposed procedure is easy to implement and can be further employed to design similar or other distinct metamaterial structures.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectEEEen_US
dc.subjectComplementary split-ring resonator (CSRR)en_US
dc.subjectParticle swarm optimization (PSO)en_US
dc.subjectMachine learning (ML)en_US
dc.titleParametric Optimization of Complementary Split-Ring Resonator Dimensions for Planar Antenna Size Miniaturizationen_US
dc.typeArticleen_US
Appears in Collections:Department of Electrical and Electronics Engineering

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