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      Dürtün gürültüye karşı sağlam küme üyeliği süzgeç algoritmaları

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      Author
      Sayın, Muhammed Ö.
      Vanlı, N. Denizcan
      Kozat, Süleyman S.
      Date
      2014-04
      Source Title
      22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings
      Publisher
      IEEE
      Pages
      1551 - 1554
      Language
      Turkish
      Type
      Conference Paper
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      Abstract
      Bu bildiride, dürtün gürültüye karşı sağlam küme üyeliği süzgeç algoritmaları öneriyoruz. İlk olarak küme üyeliği düzgelenmiş en küçük mutlak fark algoritmasını (SM-NLAD) tanıtıyoruz. Bu algoritma hatanın karesi yerine mutlak değerini maliyetlendirerek dürtün gürültüye karşı sağlamlık sağlar. Sonra bu algoritmanın dürtün gürültünün olmadığı ortamlarda da diğer algoritmalarla karşılaştırılabilir performans sergilemesi için logaritmik maliyet çerçevesinden yararlanarak küme üyeliği düzgelenmiş en küçük logaritmik mutlak fark algoritmasını (SMNLLAD) öneriyoruz. Logaritmik maliyet fonksiyonu doğal olarak büyük hata değerlerinin mutlak değerini içerirken küçük hata değerlerinin karesini içerir. Son olarak, sayısal deneylerimizde algoritmalarımızın dürtün gürültülere karşı sağlamlığını ve dürtün gürültünün olmadığı ortamlarda da karşılaştırılabilir performans sergilediğini gösteriyoruz.
       
      In this paper, we propose robust set-membership filtering algorithms against impulsive noise. Firstly, we introduce set-membership normalized least absolute difference algorithm (SM-NLAD). This algorithm provides robustness against impulsive noise through pricing the absolute error instead of the square. Then, in order to achieve comparable convergence performance in the impulse-free noise environments, we propose the set-membership normalized least logarithmic absolute difference algorithm (SM-NLLAD) through the logarithmic cost framework. Logarithmic cost function involves the absolute value of the error for large error values and the square of the error for small error values intrinsically. Finally, in the numerical examples, we show the robustness of our algorithms against impulsive noise and their comparable performance in the impulse-free noise environments. © 2014 IEEE.
      Keywords
      Impulsive noise
      Logarithmic error cost
      Robust adaptive filtering
      Set membership filtering
      Adaptive filtering
      Costs
      Signal processing
      Absolute difference
      Absolute error
      Absolute values
      Convergence performance
      Filtering algorithm
      Noise environments
      Set membership filtering
      Set-membership
      Algorithms
      Permalink
      http://hdl.handle.net/11693/27877
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/SIU.2014.6830538
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      • Department of Electrical and Electronics Engineering 3613
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