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This work addresses the dynamical inverse problem of EEG source reconstruction by using two main approaches: Dynamic Inverse Problem solution considering Time Varying and Time invariant Constraints, and Weighted Dynamic Inverse Problem solution. Discussed approach of representation comprises two main contributions: Firstly, the introduction of a discrete--time nonlinear model grounded on physiological considerations that explains better the dynamics of the brain neural activity. Secondly, the inclusion of estimation of time varying parameters that allows the enhancement of the nonlinear...