Please use this identifier to cite or link to this item: http://localhost:80/xmlui/handle/123456789/5193
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dc.contributor.authorAkbar, Sadiq-
dc.date.accessioned2019-10-04T09:32:06Z-
dc.date.accessioned2020-04-11T15:38:21Z-
dc.date.available2020-04-11T15:38:21Z-
dc.date.issued2019-
dc.identifier.govdoc17736-
dc.identifier.urihttp://142.54.178.187:9060/xmlui/handle/123456789/5193-
dc.description.abstractParameter estimation of electromagnetic plane waves is one of the important areas of researchers since few decades. It has got direct applications in the field of radar, sonar, seismic exploration, mobile communication etc. In this dissertation, efficient and new evolutionary algorithms were designed for the parameter estimation of plane waves which include amplitude and direction of arrival. These global search optimization algorithms include Genetic Algorithm, Fractional Order Darwinian Particle Swarm optimization and Flower Pollination Algorithm etc. In order to improve the performance of global search algorithms, these were also hybridized with local search optimization techniques such as Sequential Quartic Programing. Different structures of antenna arrays were used that include uniform linear array, 1L shaped array and 2L shaped arrays for the reception of plane waves of electromagnetic nature. In order to test the validity and reliability of proposed algorithms, mean squared error was used as a fitness evaluation criterion that can be defined as a difference between the actual and estimated responses of the system. In this regard a large number of Monte Carlo simulations were carried out for the statistical analysis in terms of accuracy of estimation, convergence, robustness (against noise) and computational complexity time to validate proposed algorithms. All the simulations were carried out in MATLAB.en_US
dc.description.sponsorshipHigher Education Commission, Pakistanen_US
dc.language.isoen_USen_US
dc.publisheruniversity of Peshawar, Peshawaren_US
dc.subjectElectronicsen_US
dc.titleParameter Estimation of Electromagnetic Plane Waves Using Novel Adaptive Metaheuristic Techniquesen_US
dc.typeThesisen_US
Appears in Collections:Thesis

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