Mixture of set membership filters approach for big data signal processing

Date
2016
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Source Title
Proceedings of the IEEE 24th Signal Processing and Communications Applications Conference, SIU 2016
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Publisher
IEEE
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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.

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Keywords
Affine combination, Big data, Computational efficiency, Convex combination, Mixture of experts, Set-membership filtering
Citation
Published Version (Please cite this version)