An On-line Fisher Discriminant.
Manuel Ortega-Moral, Vanessa Gómez-Verdejo, Jerónimo Arenas‐García, Aníbal Ramón Figueiras-Vidal · 2005
Abstract. Many applications in signal processing need an adaptive algorithm. Adaptive schemes are useful when the statistics of the problem are unknown or when facing varying environments. Nonetheless, many of these applications deal with classification tasks, and most algorithms are not specifically thought to tackle these kinds of problems. Whereas Fisher’s criterion aimed to find the most adequate direction to discriminate classes in a stationary setting, the newly proposed On-line Fisher Linear Discriminant (OFLD) is able to adaptively update its parameters maintaining its discrimination goal. The algorithm has been tested in an equalization problem for several conditions. 1