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The proposed null Foley-Sammon transform (NFST) method based on the Gram-Schmidt orthogonalization successfully overcomes the so-called small sample size problem with high performance in terms of recognition accuracy and low computation cost, however, the NFST method is still a linear technique in nature, so a new nonlinear feature extraction method called kernel null Foley-Sammon transform (KNFST)...
Orthogonal discriminant analysis algorithms have recently been proposed. However, these methods donpsilat address the singularity problem in the high dimensional feature space. In this paper, we present a new method called direct orthogonal discriminant analysis (DODA), which is able to extract all the orthogonal discriminant vectors simultaneously in the high-dimensional feature space and does not...
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