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Application of Wavelet Network Combined with Nonlinear Dimensionality Reduction on the Neural Dipole Localization

  • Qing Wu
  • Lukui Shi
  • Tao Lin
  • Ping He
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4113)

Abstract

A wavelet network (WN) method is presented in this paper, which can be used to estimate the location and moment of an equivalent current dipole source using reduced-dimension data from the original measurement electroencephalography (EEG). In order to handle the large-scale high dimension problems efficiently and provide a real-time EEG dipole source localizer, the ISOMAP algorithm is firstly used to find the low dimensional manifolds from high dimensional EEG signal. Then, a WN is employed to discover the relationship between the observation potentials on the scalp and the internal sources within the brain. In our simulation experiments, satisfactory results are obtained.

Keywords

Boundary Element Method Geodesic Distance Head Model Wavelet Frame Dipole Source 
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

  • Qing Wu
    • 1
  • Lukui Shi
    • 1
  • Tao Lin
    • 1
  • Ping He
    • 1
  1. 1.School of Computer Science and SoftwareHebei University of TechnologyTianjinChina

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