The problem of extracting relevant information about a defective specimen from external non-invasive measurements is hardly solvable without exploiting recent advances in signal processing. The usual two-step NDT/NDE problem (detection and reconstruction of the defect) can be interpreted as a pattern recognition in which the feature extraction aspect is by far the most interesting from the scientific viewpoint. Some relevant feature extraction techniques are proposed, aiming to finding the most advantageous mapping that reduces the dimensionality of the input patterns while perserving the relevant information content about the defect.

Linear and non linear techniques for feature extraction from NDE data

Morabito F. C.;VERSACI M
2000

Abstract

The problem of extracting relevant information about a defective specimen from external non-invasive measurements is hardly solvable without exploiting recent advances in signal processing. The usual two-step NDT/NDE problem (detection and reconstruction of the defect) can be interpreted as a pattern recognition in which the feature extraction aspect is by far the most interesting from the scientific viewpoint. Some relevant feature extraction techniques are proposed, aiming to finding the most advantageous mapping that reduces the dimensionality of the input patterns while perserving the relevant information content about the defect.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12318/10741
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