Browsing by Subject "Noise-enhanced detection"

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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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    Noise enhanced detection in multiple-access environments
    (IEEE, 2009) Bayram, Suat; Gezici, Sinan
    Under certain conditions, addition of noise can enhance performance of suboptimal detectors, which is called the stochastic resonance (SR) effect. In this paper, the effects of SR are investigated for conventional detectors in the presence of multiple-access interference. First, conditions under which probability of error performance of the detector can or cannot be improved are obtained. Then, performance of noise enhanced detectors are analyzed, and an upper bound on the amount of performance improvement that can be obtained via SR is derived. Numerical examples are presented to support the theoretical analysis.
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    Noise enhanced detection in the restricted Bayesian framework
    (IEEE, 2010) Bayram, Suat; Gezici, Sinan; Poor H.V.
    Effects of additive independent noise are investigated for sub-optimal detectors according to the restricted Bayes criterion. The statistics of optimal additive noise are characterized. Also, sufficient conditions for improvability or nonimprovability of detection via additive noise are obtained. A detection example is presented to study the theoretical results. ©2010 IEEE.
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    Noise-enhanced M-ary hypothesis-testing in the minimax framework
    (IEEE, 2009-09) Bayram, Suat; Gezici, Sinan
    In this study, the effects of adding independent noise to observations of a suboptimal detector are studied for M-ary hypothesis-testing problems according to the minimax criterion. It is shown that the optimal additional noise can be represented by a randomization of at most M signal values under certain conditions. In addition, a convex relaxation approach is proposed to obtain an accurate approximation to the noise probability distribution in polynomial time. Furthermore, sufficient conditions are presented to determine when additional noise can or cannot improve the performance of a given detector. Finally, a numerical example is presented. © 2009 IEEE.