Diffusion LMS Strategies in Sensor Networks With Noisy Input Data

We investigate the performance of distributed least-mean square (LMS) algorithms for parameter estimation over sensor networks where the regression data of each node are corrupted by white measurement noise. Under this condition, we show that the estimates produced by distributed LMS algorithms will...

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Bibliographic Details

Published in:	IEEE/ACM transactions on networking Vol. 24; no. 1; pp. 3 - 14
Main Authors:	Abdolee, Reza, Champagne, Benoit
Format:	Journal Article
Language:	English
Published:	New York IEEE 01-02-2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithm design and analysis Algorithms Bias-compensated least-mean square (LMS) diffusion adaptation distributed parameter estimation Estimation Least squares approximations network optimization Noise Noise measurement Parameter estimation Signal processing algorithms Vectors
Online Access:	Get full text
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