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Localization of P300 Sources in Schizophrenia Patients Using Constrained BSS

  • Saeid Sanei
  • Loukianos Spyrou
  • Wenwu Wang
  • Jonathon A. Chambers
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3195)

Abstract

A robust constrained blind source separation (CBSS) algorithm has been proposed for separation and localization of the P300 sources in schizophrenia patients. The algorithm is an extension of the Infomax algorithm, based on minimization of mutual information, for which a reference P300 signal is used as a constraint. The reference signal forces the unmixing matrix to separate the sources of both auditory and visual P300 resulted from the corresponding stimulations. The constrained problem is then converted to an unconstrained problem by means of a set of nonlinear penalty functions. This leads to the modification of the overall cost function, based on the natural gradient algorithm (NGA). The P300 sources are then localized based on electrode – source correlations.

Keywords

Mutual Information Reference Signal Schizophrenia Patient P300 Amplitude Independent Component Analysis 
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 2004

Authors and Affiliations

  • Saeid Sanei
    • 1
  • Loukianos Spyrou
    • 1
  • Wenwu Wang
    • 2
  • Jonathon A. Chambers
    • 2
  1. 1.Centre for Digital Signal Processing ResearchKing’s College LondonUK
  2. 2.Communications and Information Technologies Research Group, Cardiff School of EngineeringCardiff UniversityCardiffUK

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