Article (Scientific journals)
Normalized LMS Algorithm and Data-selective Strategies for Adaptive Graph Signal Estimation
Jorge Mendes Spelta, Marcelo; Alves Martins, Wallace
2019In Signal Processing
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Preprint submitted to (on September 3, 2019) and accepted by (on September 30, 2019) the journal "Signal Processing" from EURASIP. The original publication is available at

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Keywords :
Graph signal processing; Graph signal estimation; data-selective algorithms
Abstract :
[en] This work proposes a normalized least-mean-squares (NLMS) algorithm for online estimation of bandlimited graph signals (GS) using a reduced number of noisy measurements. As in the classical adaptive filtering framework, the resulting GS estimation technique converges faster than the least-mean-squares (LMS) algorithm while being less complex than the recursive least-squares (RLS) algorithm, both recently recast as adaptive estimation strategies for the GS framework. Detailed steady-state mean-squared error and deviation analyses are provided for the proposed NLMS algorithm, and are also employed to complement previous analyses on the LMS and RLS algorithms. Additionally, two different time-domain data-selective (DS) strategies are proposed to reduce the overall computational complexity by only performing updates when the input signal brings enough innovation. The parameter setting of the algorithms is performed based on the analysis of these DS strategies, and closed formulas are derived for an accurate evaluation of the update probability when using different adaptive algorithms. The theoretical results predicted in this work are corroborated with high accuracy by numerical simulations.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Jorge Mendes Spelta, Marcelo;  Federal University of Rio de Janeiro (UFRJ) > Electrical Engineering Program (PEE/Coppe)
Alves Martins, Wallace ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
External co-authors :
Language :
Title :
Normalized LMS Algorithm and Data-selective Strategies for Adaptive Graph Signal Estimation
Publication date :
Journal title :
Signal Processing
Publisher :
Elsevier, Netherlands
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Security, Reliability and Trust
European Projects :
H2020 - 742648 - AGNOSTIC - Actively Enhanced Cognition based Framework for Design of Complex Systems
Funders :
CE - Commission Européenne [BE]
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