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.