A New Refinement-Free Preconditioner for the Symmetric Formulation in Electroencephalography
Résumé
Widely employed for the accurate solution of the
electroencephalography forward problem, the symmetric formu-
lation gives rise to a first kind, ill-conditioned operator ill-
suited for complex modelling scenarios. This work presents a
novel preconditioning strategy based on an accurate spectral
analysis of the operators involved which, differently from other
Calderón-based approaches, does not necessitate the barycentric
refinement of the primal mesh (i.e., no dual matrix is required).
The discretization of the new formulation gives rise to a well-
conditioned, symmetric, positive-definite system matrix, which
can be efficiently solved via fast iterative techniques. Numerical
results for both canonical and realistic head models validate the
effectiveness of the proposed formulation.