Kılıç, O. FatihSayın, M. ÖmerDelibalta, İ.Kozat, Süleyman Serdar2018-04-122018-04-122016http://hdl.handle.net/11693/37703Date of Conference: 16-19 May 2016Conference Name: IEEE 24th Signal Processing and Communications Applications Conference, SIU 2016In 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.TurkishAffine combinationBig dataComputational efficiencyConvex combinationMixture of expertsSet-membership filteringMixture of set membership filters approach for big data signal processingBüyük veri sinyal işlemesi için küme üyeliği süzgeç birleşimi yaklaşımıConference Paper10.1109/SIU.2016.7495965