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Feature extraction by identification of a parameterized system model

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2 Author(s)
Fehlauer, J. ; Bell Laboratories, Holmdel, NJ, USA ; Eisenstein, B.

This paper focuses on extracting features from time series for pattern recognition. System identification techniques are used to represent the signals by a parameterized system model (PSM) with the parameter vector describing the PSM becoming the feature vector. A deconvolution procedure is used to enhance pattern class discrimination. The advantages of the PSM approach is a reduction of the dimensionality of the feature space thereby simplifying the classifier design and evaluation. The PSM feature extraction technique is applied to a flaw characterization problem arising from ultrasonic nondestructive testing of materials.

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Automatic Control, IEEE Transactions on  (Volume:26 ,  Issue: 2 )