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Identification and Extraction of Evoked Potentials Based on Borel Spectral Measure for Less Trial Mixtures

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Advances in Neural Networks - ISNN 2008 (ISNN 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5264))

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Abstract

A new method for identifying the independent components of an alpha-stable random vector for under-determined mixtures is proposed. The method is based on an estimate of the discrete Borel measure for the characteristic function of an alpha-stable random vector. Simulations demonstrate that the proposed method can identify the basis vectors of evoked potentials in the so-called under-determined case of more sources than mixtures.

This work is supported by National Science Foundation of China under Grant 60772037 and Science Foundation of Department of Health of Jiangxi province under Grant 20072048.

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Author information

Authors and Affiliations

  1. College of Electronic Engineering, Jiujiang University, 332005, Jiujiang, China

    Daifeng Zha

Authors
  1. Daifeng Zha
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghu University, 100084, Beijing, China

    Fuchun Sun

  2. Institute TAMS (Technical Aspects of Multimodal Systems), department of Informatics, University of Hamburg, Vogt-Koelln-Straße 30, 22527, Hamburg, Germany

    Jianwei Zhang

  3. Intel China Research Center, 8/F, Peking University, Department of Machine Intelligence, 100871, Beijing, China

    Ying Tan

  4. Department of Mathematics, Southeast University, 210096, Nanjing, China

    Jinde Cao

  5. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

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© 2008 Springer-Verlag Berlin Heidelberg

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Zha, D. (2008). Identification and Extraction of Evoked Potentials Based on Borel Spectral Measure for Less Trial Mixtures. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds) Advances in Neural Networks - ISNN 2008. ISNN 2008. Lecture Notes in Computer Science, vol 5264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87734-9_85

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  • DOI: https://doi.org/10.1007/978-3-540-87734-9_85

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87733-2

  • Online ISBN: 978-3-540-87734-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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