Method of geometric linear discriminant analysis pattern recognition

Method of geometric linear discriminant analysis pattern recognition

Feature attributes are extracted from an observation space to create feature vectors for each class to be identified. A linear transformation matrix is used to reduce the dimension of the feature vectors. A numerical optimization algorithm maximizes a geometric criterion function in order to calcula...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: ORDOWSKI MARK LAWRENCE, MEYER GERARD G. L
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTING
COUNTING
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
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Beschreibung
Zusammenfassung:Feature attributes are extracted from an observation space to create feature vectors for each class to be identified. A linear transformation matrix is used to reduce the dimension of the feature vectors. A numerical optimization algorithm maximizes a geometric criterion function in order to calculate the linear transformation matrix, where it exploits the geometry of the class contours of constant density. Next, a classifier based on the feature vectors in a lower dimension is generated and a class is determined for the data represented.