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2010, Volume 4, Issue 1: 169-190. Doi: 10.3934/ipi.2010.4.169
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Particle filtering, beamforming and multiple signal classification for the analysis of magnetoencephalography time series: a comparison of algorithms

  • 1.

    Dipartimento di Matematica, Università di Genova, via Dodecaneso 35 16146 Genova

  • 2.

    CNR - INFM LAMIA, via Dodecaneso 33 16146 Genova

Received:  October 2008
Revised:  December 2009
Published:  February 2010
Abstract Related Papers Cited by
    Abstract
  • We present a comparison of three methods for the solution of the magnetoencephalography inverse problem. The methods are: a linearly constrained minimum variance beamformer, an algorithm implementing multiple signal classification with recursively applied projection and a particle filter for Bayesian tracking. Synthetic data with neurophysiological significance are analyzed by the three methods to recover position, orientation and amplitude of the active sources. Finally, a real data set evoked by a simple auditory stimulus is considered.
    Mathematics Subject Classification: Primary: 65R32; Secondary: 65C05.

    Citation:
    shu

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