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Comparing the Performance of Solvers for a Bioelectric Field Problem

  • Marcus Mohr
  • Bart Vanrumste
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2330)

Abstract

The model-based reconstruction of electrical brain activity from electroencephalographic measurements is of constantly growing importance in the fields of Neurology and Neurosurgery. Algorithms for this task involve the solution of a 3D Poisson problem on a complicated geometry and with non-continuous coefficients for a considerable number of different right hand sides. Thus efficient solvers for this subtask are required. We will report on our experiences with different iterative solvers, Successive Overrelaxation, (Preconditioned) Conjugate Gradients, and Algebraic Multigrid, for a discretisation based on cell-centred finite-differences.

Keywords

Conjugate Gradient Multigrid Method Forward Problem Iterative Solver Krylov Subspace Method 
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 2002

Authors and Affiliations

  • Marcus Mohr
    • 1
  • Bart Vanrumste
    • 2
  1. 1.System Simulation Group of the Computer Science DepartmentFriedrich-Alexander-University Erlangen-NurembergGermany
  2. 2.Electrical and Computer EngineeringUniversity of CanterburyUK

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