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Application of independent component analysis for evaluation of ashlar masonry walls

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Application of independent component analysis for evaluation of ashlar masonry walls

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Salazar Afanador, A.; Safont Armero, G.; Vergara Domínguez, L. (2011). Application of independent component analysis for evaluation of ashlar masonry walls. Lecture Notes in Computer Science. 6691(1):469-476. https://doi.org/10.1007/978-3-642-21498-1_59

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Metadatos del ítem

Título: Application of independent component analysis for evaluation of ashlar masonry walls
Autor: Salazar Afanador, Addisson Safont Armero, Gonzalo Vergara Domínguez, Luís
Entidad UPV: 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
Fecha difusión:
Resumen:
[EN] This paper presents a novel application of Independent Component Analysis (ICA) to the evaluation of ashlar masonry walls inspected with Ground Penetrating Radar (GPR). ICA is used as preprocessor to eliminate ...[+]
Palabras clave: ICA , GPR , NDT , Clutter
Derechos de uso: Reserva de todos los derechos
ISBN: 978-3-642-21497-4 (Print) 978-3-642-21498-1 (Online)
Fuente:
Lecture Notes in Computer Science. (issn: 0302-9743 )
DOI: 10.1007/978-3-642-21498-1_59
Editorial:
Springer Verlag (Germany)
Versión del editor: http://dx.doi.org/10.1007/978-3-642-21498-1_59
Código del Proyecto:
info:eu-repo/grantAgreement/GVA//PROMETEO%2F2010%2F040/
info:eu-repo/grantAgreement/MICINN//TEC2008-02975/ES/PROCESADOR NO-LINEAL DE MEZCLAS CON APLICACION EN DETECCION, CLASIFICACION, FILTRADO Y PREDICCION/
Agradecimientos:
This work has been supported by the Generalitat Valenciana under grant PROMETEO/2010/040, and the Spanish Administration and the FEDER Programme of the European Union under grant TEC 2008-02975/TEC.
Tipo: Artículo

References

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Salazar, A., Unió, J.M., Serrano, A., Gosalbez, J.: Neural networks for defect detection in non-destructive evaluation by sonic signals. In: Sandoval, F., Prieto, A.G., Cabestany, J., Graña, M. (eds.) IWANN 2007. LNCS, vol. 4507, pp. 638–645. Springer, Heidelberg (2007)

Salazar, A., Vergara, L., Llinares, R.: Learning material defect patterns by separating mixtures of independent component analyzers from NDT sonic signals. Mechanical Systems and Signal processing 24(6), 1870–1886 (2010)

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