Advertisement

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)

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.

Keywords

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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Chatterjee, C., Roychowdhury, V.P.: On Self Organizing Algorithm and Networks for Class Separability Features. IEEE Trans. Neural Net. 8, 663–678 (1997)CrossRefGoogle Scholar
  2. 2.
    Lin, R., Yang, M., Stephen, E.L.: Object Tracking Using Incremental Fisher Discriminant Analysis. In: ICPR, vol. (2), pp. 757–760 (2004)Google Scholar
  3. 3.
    Yan, J., Zhang, B., Yan, S., Yang, Q., Li, H., Chen, Z., Xi, W., Fan, W., Ma, W., Cheng, Q.: IMMC: Incremental Maximum Margin Criterion. In: KDD, pp. 725–730 (2004)Google Scholar
  4. 4.
    Pang, S., Ozawa, S., Kasabov, N.: Incremental Linear Discriminant Analysis for Classification of Data Streams. IEEE Trans. Syst., Man, and Cybern. B 35(5), 905–914 (2005)CrossRefGoogle Scholar
  5. 5.
    Chatterjee, C.: Adaptive Algorithms for First Principal Eigenvector Computation. Neural Networks 18(2), 145–159 (2005)MATHCrossRefGoogle Scholar
  6. 6.
    Fisher, R.A.: The Use of Multiple Measurements in Taxonomic Problems. Annals of Eugenics 7, 179–188 (1936)Google Scholar
  7. 7.
    Fukunaga, K.: Introduction to Statistical Pattern Recognition. Academic Press, London (1990)MATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

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

Personalised recommendations