An optimal orthonormal system for discriminant analysis

摘要

This paper proposes a new discriminant analysis with orthonormal coordinate axes of the feature space. In general, the number of coordinate axes of the feature space in the traditional discriminant analysis depends on the number of pattern classes. Therefore, the discriminatory capability of the feature space is limited considerably. The new discriminant analysis solves this problem completely. In addition, it is more powerful than the traditional one in so far as the discriminatory power and the mean error probability for coordinate axes are concerned. This is also shown by a numerical example.