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      • Department of Electrical and Electronics Engineering
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      Mixture of set membership filters approach for big data signal processing

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      Author(s)
      Kılıç, O. Fatih
      Sayın, M. Ömer
      Delibalta, İ.
      Kozat, Süleyman Serdar
      Date
      2016
      Source Title
      Proceedings of the IEEE 24th Signal Processing and Communications Applications Conference, SIU 2016
      Publisher
      IEEE
      Pages
      1217 - 1220
      Language
      Turkish
      Type
      Conference Paper
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      Abstract
      In this work, we propose a new approach for mixture of adaptive filters based on set-membership filters (SMF) which is specifically designated for big data signal processing applications. By using this approach, we achieve significantly reduced computational load for the mixture methods with better performance in convergence rate and steady-state error with respect to conventional mixture methods. Finally, we approve these statements with the simulations done on produce data.
      Keywords
      Affine combination
      Big data
      Computational efficiency
      Convex combination
      Mixture of experts
      Set-membership filtering
      Permalink
      http://hdl.handle.net/11693/37703
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/SIU.2016.7495965
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      • Department of Electrical and Electronics Engineering 4011
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