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International Symposium on Neural Networks

ISNN 2004: Advances in Neural Networks – ISNN 2004 pp 732–737Cite as

Single-Trial Estimation of Multi-channel VEP Signals Using Independent Component Analysis

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3173))

Abstract

Single-trial estimation of visual evoked potential (VEP) became a very interesting and challenge problem in biomedical signal processing at present. A method based on the independent component analysis (ICA) was proposed for single-trial detection of multi-channel VEP signals contaminated with background electroencephalograph (EEG). It achieved the satisfied results to show that the presented ICA method can be as an effective tool for single-trial VEP signal estimation in low SNR situation.

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Author information

Authors and Affiliations

  1. Key Lab. of Guangdong, Shantou University, Guangdong, 515063, China

    Lisha Sun, Minfen Shen & Weiling Xu

  2. Dept. of Electronic Engineering, Hong Kong University, Hong Kong

    Francis Chan

Authors
  1. Lisha Sun
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  2. Minfen Shen
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  3. Weiling Xu
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  4. Francis Chan
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Editor information

Editors and Affiliations

  1. School of Electronic and Information Engineering, Dalian University of Technology, 116023, Dalian, China

    Fu-Liang Yin

  2. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  3. School of Electronic and Information Engineering, Dalian University of Technology, 116023, Dalian, Liaoning, China

    Chengan Guo

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© 2004 Springer-Verlag Berlin Heidelberg

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Cite this paper

Sun, L., Shen, M., Xu, W., Chan, F. (2004). Single-Trial Estimation of Multi-channel VEP Signals Using Independent Component Analysis. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks – ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28647-9_120

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  • DOI: https://doi.org/10.1007/978-3-540-28647-9_120

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22841-7

  • Online ISBN: 978-3-540-28647-9

  • eBook Packages: Springer Book Archive

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