A novel KLT algorithm optimized for small signal sets

Karhunen-Loève Transform, being able to represent stochastic processes under appropriate conditions, is a powerful signal processing tool. But the high computational cost incurred in the modeling of long signals has limited its use in the recognition of speech segmented at the word level. In this paper we present a novel algorithm that significantly reduces the computational cost when the number of signals to be treated is small in comparison to their samples