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dc.contributor.authorVakula, Damera-
dc.contributor.authorSarma, N.V.S.N-
dc.date.accessioned2024-11-19T06:07:24Z-
dc.date.available2024-11-19T06:07:24Z-
dc.date.issued2008-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/1530-
dc.descriptionNITWen_US
dc.description.abstractA novel approach using Artificial Neural network (ANN) is proposed to identify the faulty elements present in a non uniform linear array. The input to the neural network is amplitude of radiation pattern and output of neural network is the location of faulty elements. In this work, ANN is implemented with two algorithms; Radial Basis Function neural network (RBF) and Probabilistic neural network and their performance is compared. The network is trained with some of the possible faulty radiation patterns and tested with various measurement errors. It is proved that the method gives a high success rate.en_US
dc.language.isoenen_US
dc.publisherProceedings of the International Conference on Electromagnetic Interference and Compatibilityen_US
dc.subjectNeural Networken_US
dc.subjectDiagnose Faultsen_US
dc.subjectLinear Antennaen_US
dc.subjectArrayen_US
dc.titleNeural Network Approach To Diagnose Faults In Linear Antenna Arrayen_US
dc.typeOtheren_US
Appears in Collections:Electronics and Communication Engineering

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