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Robust Distributed Clustering Algorithm Over Multitask Networks

Title
Robust Distributed Clustering Algorithm Over Multitask Networks
Authors
Kong, Jun-TaekAhn, Do-ChangKim, Seong-EunSong, Woo-Jin
Date Issued
Aug-2018
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
We propose a new adaptive clustering algorithm that is robust to various multitask environments. Positional relationships among optimal vectors and a reference signal are determined by using the mean-square deviation relation derived from a one-step least-mean-square update. Clustering is performed by combining determinations on the positional relationships at several iterations. From this geometrical basis, unlike the conventional clustering algorithms using simple thresholding method, the proposed algorithm can perform clustering accurately in various multitask environments. Simulation results show that the proposed algorithm has more accurate estimation accuracy than the conventional algorithms and is insensitive to parameter selection.
URI
http://oasis.postech.ac.kr/handle/2014.oak/95698
ISSN
2169-3536
Article Type
Article
Citation
IEEE Access, vol. 6, page. 45439 - 45447, 2018-08
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 SONG, WOO JIN
Dept of Electrical Enginrg
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