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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. doi:10.1007/978-3-642-21498-1_59

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/58588

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Title: Application of independent component analysis for evaluation of ashlar masonry walls
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
Issued date:
Abstract:
[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 ...[+]
Subjects: ICA , GPR , NDT , Clutter
Copyrigths: Reserva de todos los derechos
ISBN: 978-3-642-21497-4 (Print) 978-3-642-21498-1 (Online)
Source:
Lecture Notes in Computer Science. (issn: 0302-9743 )
DOI: 10.1007/978-3-642-21498-1_59
Publisher:
Springer Verlag (Germany)
Publisher version: http://dx.doi.org/10.1007/978-3-642-21498-1_59
Thanks:
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.
Type: 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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