Browsing by Subject "Performance comparison"

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    Birleşik sezim ve kestirim sistemlerinin gürültü ile geliştirilmesi
    (IEEE, 2014-04) Akbay, Abdullah Başar; Gezici, Sinan
    Belirli koşullar altında, optimal olmayan bazı sezici ve kestiricilerin performansını girdilerine gürültü ekleyerek geliştirmek mümkündür. Bu çalışmada, birleşik bir sezim ve kestirim sisteminin gürültü eklenerek geliştirilmesi incelenmektedir. Sistem performansının maksimizasyonu bir optimizasyon problemi olarak tanımlanmaktadır. Optimal toplanır gürültü dağılımının istatiksel özellikleri belirlenmektedir. Sistem performansının gürültü ile iyileştirilemeyeceği bir koşul elde edilmektedir.Önerilen optimizasyon probleminin, bir doğrusal programlama (DP) problemi olarak yaklaşımı sunulmaktadır. Bir sayısal örnek üzerinde, kuramsal bulguları desteklemek amacıyla, gürültü eklenmiş sistem ile orijinal sistemin performansları karşılaştırılmaktadır.
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    A performance comparison of zone-based multicast protocols for mobile ad hoc networks
    (IEEE, 2003) Zhang, Y.; Rangnekar, A.; Selçuk, Ali A.; Bicak, A.; Sidhu, D.
    With the current trend toward ubiquitous computing come wireless devices capable of forming the nodes of mobile ad hoc networks. Such networks typically rely on routing protocols in order to communicate messages from a source node to a destination node through a set of intermediary nodes. In a typical ad hoc environment, mobile nodes mostly work as a group and are involved in collaborative computing. Multicast communication is more effective in these scenarios. This paper presents the comparison of the performance of two zone-based multicast routing protocols. Shared-tree MZR is a shared tree variant of the Multicast Routing Protocol based on Zone Routing (MZR). We compare the two variants and analyze their performance under various network conditions. The test results show that Shared-tree MZR protocol performs well and has significantly low overhead in scenarios with multiple sources. ©2003 IEEE.
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    Signal denoising by piecewise continuous polynomial fitting
    (IEEE, 2010) Yıldız, Aykut; Arıkan, Orhan
    Piecewise smooth signal denoising is cast as a non-linear optimization problem in terms of transition boundaries and a parametric smooth signal family. Optimal transition boundaries for a given number of transitions are obtained by using particle swarm optimization. The piecewise smooth section parameters are obtained as the maximum likelihood estimates conditioned on the optimal transition boundaries. The proposed algorithm is extended to the case where the number of transition boundaries are unknown by sequentially increasing number of sections until the residual error is at the level of noise standard deviation. Performance comparison with the state of the art techniques reveals the important advantages of the proposed technique. ©2010 IEEE.