Study of Robust Diffusion Recursive Least Squares Algorithms with Side Information for Networked Agents

This work develops a robust diffusion recursive least squares algorithm to mitigate the performance degradation often experienced in networks of agents in the presence of impulsive noise. This algorithm minimizes an exponentially weighted least-squares cost function subject to a time-dependent const...

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Bibliographic Details
Published in:arXiv.org
Main Authors: Y Yu, de Lamare, R C, Zakharov, Y
Format: Paper
Language:English
Published: Ithaca Cornell University Library, arXiv.org 24.12.2018
Subjects:
Algorithms
Computer simulation
Diffusion
Least squares
Parameter estimation
Performance degradation
Time dependence
ISSN:2331-8422
Online Access:Get full text
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Summary:This work develops a robust diffusion recursive least squares algorithm to mitigate the performance degradation often experienced in networks of agents in the presence of impulsive noise. This algorithm minimizes an exponentially weighted least-squares cost function subject to a time-dependent constraint on the squared norm of the intermediate estimate update at each node. With the help of side information, the constraint is recursively updated in a diffusion strategy. Moreover, a control strategy for resetting the constraint is also proposed to retain good tracking capability when the estimated parameters suddenly change. Simulations show the superiority of the proposed algorithm over previously reported techniques in various impulsive noise scenarios.
Bibliography:SourceType-Working Papers-1
ObjectType-Working Paper/Pre-Print-1
content type line 50
ISSN:2331-8422
DOI:10.48550/arxiv.1812.09985