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Comparison of two robust PCA methods for damage detection in the presence of outliers

Autor
Gharibnezhad, F.; Mujica, L.E.; Rodellar, J.
Tipus d'activitat
Article en revista
Revista
Journal of physics: conference series
Data de publicació
2011-07-19
Volum
305
Número
012009
Pàgina inicial
1
Pàgina final
10
DOI
https://doi.org/10.1088/1742-6596/305/1/012013 Obrir en finestra nova
Projecte finançador
ESTRUCTURAS AERONAUTICAS INTELIGENTES: DESARROLLO Y VALIDACION DE TECNICAS DE DETECCION DE DEFECTOS BASADAS EN RECONOCIMIENTO DE PAT
Repositori
http://hdl.handle.net/2117/14725 Obrir en finestra nova
URL
http://iopscience.iop.org/1742-6596/305/1/012009/pdf/1742-6596_305_1_012009.pdf Obrir en finestra nova
Resum
Statistical methods such as Principal Component Analysis (PCA) are suffering from contaminated data. For instance, variance and covariance as vital parts of PCA method are sensitive to anomalous observation called outliers. Outliers, who are usually, appear due to experimental errors, are observations that lie at a considerable distance from the bulk of the observations. An effective way to deal with this problem is to apply a robust, i.e. not sensitive to outliers, variant of PCA. In this work,...
Citació
Gharibnezhad, F.; Mujica, L.E.; Rodellar, J. Comparison of two robust PCA methods for damage detection in the presence of outliers. "Journal of Physics: Conference Series", 19 Juliol 2011, vol. 305, núm. 012009, p. 1-10.
Grup de recerca
CoDAlab - Control, Modelització, Identificació i Aplicacions

Participants