The null space of the within-class scatter matrix is found to express most discriminative information for the small sample size problem (SSSP). The null space-based LDA takes full ...
Kernel Fisher Discriminant Analysis (KFDA) has achieved great success in pattern recognition recently. However, the training process of KFDA is too time consuming (even intractabl...
The null space-based LDA takes full advantage of the null space while the other methods remove the null space. It proves to be optimal in performance. From the theoretical analysi...