An incremental linear discriminant analysis using fixed point method

Abstract

Linear Discriminant Analysis (LDA) is a very powerful method in pattern recognition. But it is difficult to realize online processing for data stream. In this paper, a new adaptive LDA method is proposed. We decompose the online LDA problem into two adaptive PCA problems and develop a fixed point adaptive PCA to implement adaptive LDA. Online updating of in-class scatter matrix S w (t) and covariance matrix C x (t) are derived in this paper. Simulation results show that the proposed method has no learning rate, fast convergence and less time-consuming. © Springer-Verlag Berlin Heidelberg 2006.