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Two-Stage Temporally Correlated Source Extraction Algorithm with Its Application in Extraction of Event-Related Potentials

  • Zhi-Lin Zhang
  • Liqing Zhang
  • Xiu-Ling Wu
  • Jie Li
  • Qibin Zhao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4233)

Abstract

To extract source signals with certain temporal structures, such as periodicity, we propose a two-stage extraction algorithm. Its first stage uses the autocorrelation property of the desired source signal, and the second stage exploits the independence assumption. The algorithm is suitable to extract periodic or quasi-periodic source signals, without requiring that they have distinct periods. It outperforms many existing algorithms in many aspects, confirmed by simulations. Finally, we use the proposed algorithm to extract the components of visual event-related potentials evoked by three geometrical figure stimuli, and the classification accuracy based on the extracted components achieves 93.2%.

Keywords

Source Signal Independent Component Analysis Extraction Algorithm Blind Source Separation Fundamental Period 
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

  • Zhi-Lin Zhang
    • 1
    • 2
  • Liqing Zhang
    • 1
  • Xiu-Ling Wu
    • 1
  • Jie Li
    • 1
  • Qibin Zhao
    • 1
  1. 1.Department of Computer Science and EngineeringShanghai Jiao Tong UniversityShanghaiChina
  2. 2.School of Computer Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengduChina

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