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Estimating the Laplacian matrix of Gaussian mixtures for signal processing on graphs

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Estimating the Laplacian matrix of Gaussian mixtures for signal processing on graphs

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Belda, J.; Vergara Domínguez, L.; Salazar Afanador, A.; Safont Armero, G. (2018). Estimating the Laplacian matrix of Gaussian mixtures for signal processing on graphs. Signal Processing. 148:241-249. https://doi.org/10.1016/j.sigpro.2018.02.017

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/121393

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Title: Estimating the Laplacian matrix of Gaussian mixtures for signal processing on graphs
Author:
UPV Unit: Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia
Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
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Abstract:
[EN] Recent works in signal processing on graphs have been driven to estimate the precision matrix and to use it as the graph Laplacian matrix. The normalized elements of the precision matrix are the partial correlation ...[+]
Copyrigths: Embargado
Source:
Signal Processing. (issn: 0165-1684 )
DOI: 10.1016/j.sigpro.2018.02.017
Publisher:
Elsevier
Publisher version: http://doi.org/10.1016/j.sigpro.2018.02.017
Thanks:
This work was supported by Spanish Administration (Ministerio de Economia y Competitividad) and European Union (FEDER) under grant TEC2014-58438-R, and Generalitat Valenciana under grant PROMETEO II/2014/032.
Type: Artículo

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