The aim of this paper is to propose a least mean squares (LMS) strategy for adaptive estimation of signals defined over graphs. Assuming the graph signal to be band-limited, over a known bandwidth, the method enables reconstruction, with guaranteed performance in terms of mean-square error, and tracking from a limited number of observations sampled over a subset of vertices. A detailed mean square analysis provides the performance of the proposed method, and leads to several insights for designing useful sampling strategies for graph signals. Numerical results validate our theoretical findings, and illustrate the advantages achieved by the proposed strategy for online estimation of band-limited graph signals. © 2016 IEEE.

LMS estimation of signals defined over graphs / Di Lorenzo, Paolo; BARBAROSSA, Sergio; Banelli, Paolo; SARDELLITTI, Stefania. - ELETTRONICO. - (2016), pp. 2121-2125. ((Intervento presentato al convegno 24th European Signal Processing Conference, EUSIPCO 2016 tenutosi a Budapest; Hungary [10.1109/EUSIPCO.2016.7760623].

LMS estimation of signals defined over graphs

Di Lorenzo, Paolo;BARBAROSSA, Sergio;SARDELLITTI, Stefania
2016

Abstract

The aim of this paper is to propose a least mean squares (LMS) strategy for adaptive estimation of signals defined over graphs. Assuming the graph signal to be band-limited, over a known bandwidth, the method enables reconstruction, with guaranteed performance in terms of mean-square error, and tracking from a limited number of observations sampled over a subset of vertices. A detailed mean square analysis provides the performance of the proposed method, and leads to several insights for designing useful sampling strategies for graph signals. Numerical results validate our theoretical findings, and illustrate the advantages achieved by the proposed strategy for online estimation of band-limited graph signals. © 2016 IEEE.
9780992862657
File allegati a questo prodotto
File Dimensione Formato  
Dilorenzo_LMS_2016.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 140.87 kB
Formato Adobe PDF
140.87 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11573/958810
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact