Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/57474
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dc.contributor.authorSrikala, E V S D N S L K-
dc.contributor.authorMurali, M-
dc.contributor.authorKrishna, M Vamshi-
dc.contributor.authorRaju, G S N-
dc.date.accessioned2021-06-14T06:58:53Z-
dc.date.available2021-06-14T06:58:53Z-
dc.date.issued2021-04-
dc.identifier.issn0975-1084 (Online); 0022-4456 (Print)-
dc.identifier.urihttp://nopr.niscair.res.in/handle/123456789/57474-
dc.description354-359en_US
dc.description.abstractIn this paper, optimization of the linear array (LA) antenna is performed using modified social group optimization algorithm (SGOA). First step of the work involves in transforming the electromagnetic engineering problem to an optimization problem which is completely described in terms of objectives. Linear array synthesis is inherently considered as a multi-attribute problem. The pattern synthesis of LA is carried out with several objectives involving sidelobe level (SLL), beam-width (BW) and desired nulls. The SLL suppression with BW constraint is considered as first objective of this work and the results are compared with several evolutionary computing algorithms like ant lion (ALO), grey wolf (GWO) and root-runner (RRA). Following this, the MSGOA is further used to synthesise null patterns in which the pattern is completely described in terms of nulls with SLL and BW as constraints. The entire simulation-based experimentation is performed using MatlabĀ® on i5 computing system.en_US
dc.language.isoen_USen_US
dc.publisherNISCAIR-CSIR, Indiaen_US
dc.rights CC Attribution-Noncommercial-No Derivative Works 2.5 Indiaen_US
dc.sourceJSIR Vol.80(04) [April 2021]en_US
dc.subjectLinear arraysen_US
dc.subjectMSGOAen_US
dc.subjectOptimizationen_US
dc.subjectPatternsen_US
dc.subjectSidelobe levelsen_US
dc.titleOptimization of Linear Arrays using Modified Social Group Optimization Algorithmen_US
dc.typeArticleen_US
Appears in Collections:JSIR Vol.80(04) [April 2021]

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