A novel method for Fisher discriminant analysis

A novel model for Fisher discriminant analysis is developed in this paper. In the new model, maximal Fisher criterion values of discriminant vectors and minimal statistical correlation between feature components extracted by discriminant vectors are simultaneously required. Then the model is transformed into an extreme value problem, in the form of an evaluation function. Based on the evaluation function, optimal discriminant vectors are worked out. Experiments show that the method presented in this paper is comparative to the winner between FSLDA and ULDA.