  We propose alternative discriminant measures for selecting the best basis
among a large collection of orthonormal bases for classification purposes. A
generalization of the Local Discriminant Basis Algorithm of Saito and Coifman
is constructed. The success of these new methods is evaluated and compared to
earlier methods in experiments.
