Multitask Diffusion Adaptation Over Asynchronous Networks

The multitask diffusion LMS is an efficient strategy to simultaneously infer, in a collaborative manner, multiple parameter vectors. Existing works on multitask problems assume that all agents respond to data synchronously. In several applications, agents may not be able to act synchronously because networks can be subject to several sources of uncertainties such as changing topology, random link failures, or agents turning on and off for energy conservation. In this paper, we describe a model for the solution of multitask problems over asynchronous networks and carry out a detailed mean and mean-square error analysis. Results show that sufficiently small step-sizes can still ensure both stability and performance. Simulations and illustrative examples are provided to verify the theoretical findings.


Published in:
IEEE Transactions on Signal Processing, 64, 11, 2835-2850
Year:
2016
Publisher:
IEEE
ISSN:
1941-0476
Laboratories:




 Record created 2017-12-19, last modified 2018-03-17


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