An Incremental Linear Discriminant Analysis Using Fixed Point Method

  • Dongyue Chen
  • Liming Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3971)


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.


Data Stream Linear Discriminant Analysis Gradient Descent Gradient Descent Method Iteration Formula 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Dongyue Chen
    • 1
  • Liming Zhang
    • 1
  1. 1.Electronic Engineer DepartmentFudan UniversityShanghaiChina

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