Parallel optimization applied to magnetoencephalography

This paper studies a new numerical scheme applicable to magnetoencephalography (MEG), that is, clustering. This method is based on a new theory to the under-determined ill-posed problem, called parallel optimization, and clusters several electric current elements distributed in a volume conductor by one point in time data, without prescribing the number of dipoles. Numerical experiments and optional algorithms are also included.