Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/34917
Title: An efficient method for computing orthogonal discriminant vectors
Authors: Wang, J
Xu, Y
Zhang, D 
You, J 
Keywords: Fisher discriminant analysis
Pattern recognition
Orthogonal discriminant vectors
Dimension reduction
Issue Date: 2010
Publisher: Elsevier
Source: Neurocomputing, 2010, v. 73, no. 10-12, p. 2168-2176 How to cite?
Journal: Neurocomputing
Abstract: We propose a linear discriminant analysis method. In this method, every discriminant vector, except for the first one, is worked out by maximizing a Fisher criterion defined in a transformed space which is the null space of the previously obtained discriminant vectors. All of these discriminant vectors are used for dimension reduction. We also propose two algorithms to implement the model. Based on the algorithms, we prove that the discriminant vectors will be orthogonal if the within-class scatter matrix is not singular. The experimental results show that the proposed method is effective and efficient.
URI: http://hdl.handle.net/10397/34917
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2010.02.009
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