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Kablosuz Sensör Ağlarında Sıkıştırılmış Örnekleme

dc.contributor.advisorToker, Cenk
dc.contributor.authorÇakılcı , Ali Yasin
dc.date.accessioned2020-09-17T10:34:38Z
dc.date.issued2020
dc.date.submitted2020-06-11
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dc.identifier.urihttp://hdl.handle.net/11655/22716
dc.description.abstractCommunication is emerging as one of the most important topics of today. Data traffic has been increasing incredibly day by day. Wireless communications is convenient to use and has been widely used in daily life with an increasing penetration. Wireless Sensor Networks use sensors to sense the environment and use wireless communications to send and receive the related information. WSN consists of sensor nodes which has limited battery power and a base station to gather the observation data and process it. It is necessary to use energy efficiently in order to increase the lifetime of the network. Furthermore, the energy consumed by the network is directly related to data communication and data processing. Compressive Sampling theory has a solution at this point. If the signal is sparse in a certain transform domain, Compressive Sampling theory states that less number of measurements can be used to reconstruct the function representing the physical parameter of concern. Because of this, CS has become an important technology for WSNs. In this study, the sensor nodes in a WSN are assumed to be distributed over a geographical region using the Gauss distribution, uniform distribution, grid distribution and H-PPP distribution, and the reconstruction performance of the OMP and CoSamp algorithms are assessed over measurements taken from sampling points.tr_TR
dc.language.isoturtr_TR
dc.publisherFen Bilimleri Enstitüsütr_TR
dc.rightsinfo:eu-repo/semantics/openAccesstr_TR
dc.subjectKablosuz sensör ağlarıtr_TR
dc.subjectSıkıştırılmış algılamatr_TR
dc.subjectSıkıştırıcı veri toplamatr_TR
dc.subject.lcshElektrik-elektronik mühendisliğitr_TR
dc.titleKablosuz Sensör Ağlarında Sıkıştırılmış Örneklemetr_TR
dc.title.alternativeCompressıve Samplıng In Wıreless Sensor Networks
dc.typeinfo:eu-repo/semantics/masterThesistr_TR
dc.description.ozetHaberleşme günümüzün en önemli konularından biri olarak öne çıkmaktadır. Günden güne veri trafiği inanılmaz bir şekilde artış göstermektedir. Pratik açıdan kullanım kolaylığı ile birlikte kablosuz haberleşme teknolojisi bu zamana kadar önemli gelişmeler kat etmiştir. WSN’ler kablosuz haberleşmeyi kullanan, çeşitli fiziksel ölçümleri yapıp belli bir bölgeyi gözetlemeyi veya o bölgeden bilgi toplama imkânı veren ağlardır. Bu ağ kısıtlı enerjiye sahip düğümlerden ve bu düğümlerin verilerinin toplandığı ve işlendiği en az bir erişim noktasından oluşmaktadır. WSN’lerdeki düğümlerin yaşam sürelerini uzatmak için enerjilerinin verimli bir şekilde kullanılması gerekmektedir. Harcanan enerji, veri iletimi ve hesaplamalar ile doğrudan ilişkilidir. CS teorisi de bu noktada çözüm sunmaktadır; eğer ölçülen sinyal seyrekse, bu sinyal Nyquist oranına göre daha az sayıda ölçümle yeniden oluşturabilmektedir. Bundan dolayı CS, WSN için önemli bir tekniktir. Bu tez çalışmasında incelenen sinüzoidal, doğrusal ve ikinci derece alanlar için örnekleme noktaları tekdüze, Gauss, H-PPP ve eş aralıklı olarak seçilmiştir. Bu örnekleme noktalarından alınan ölçümler OMP ve CoSamp algoritmaları kullanılarak geri dönüşüm başarımları incelenmiştir. Düğümlerin alana rasgele dağıtılmasını öneren, bir başka deyişle örnekleme noktalarının rasgele seçildiği, tekdüze ve H-PPP dağılımları daha başarılı sonuçlar vermiştir.tr_TR
dc.contributor.departmentElektrik –Elektronik Mühendisliğitr_TR
dc.embargo.termsAcik erisimtr_TR
dc.embargo.lift2020-09-17T10:34:38Z
dc.fundingYoktr_TR


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