Fukunaga-Koontz transform for small sample size problems

In this paper, we propose the Fukunaga-Koontz Transform (FKT) as applied to small-sample size (SSS) problems and formulate a feature scatter matrix based equivalent of the FKT. We establish the classical linear discriminant analysis (LDA) analogy of the FKT and apply it to a SSS situation. We demonstrate the significant computational savings and robustness associated with our approach using a multi-class face detection proble

New routes from minimal approximation error to principal components

SCOPUS: ar.jinfo:eu-repo/semantics/publishe