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conference paper
Performance analysis of multitask diffusion adaptation over asynchronous networks
2014
48th Asilomar Conference on Signals, Systems and Computers
The multitask diffusion LMS algorithm is an efficient strategy to address distributed estimation problems that are multitask-oriented in the sense that the optimum parameter vector may not be the same for every cluster of nodes. In this work, we explore the adaptation and learning behavior of the algorithm under asynchronous conditions when networks are subject to various sources of uncertainties, including random link failures and agents turning on and off randomly. We conduct a mean-square-error performance analysis and examine how asynchronous events interfere with the learning performance.
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Type
conference paper
Authors
Publication date
2014
Publisher
Published in
48th Asilomar Conference on Signals, Systems and Computers
Start page
788
End page
792
Peer reviewed
REVIEWED
EPFL units
Event name | Event place | Event date |
Pacific Grove, CA, USA | November 2-5, 2014 | |
Available on Infoscience
December 19, 2017