1. A method comprising: (i) receiving input-output data relating to a characteristic of a system; (ii) establishing with a microprocessor an estimate of at least one hybrid state of a plurality of hybrid states of the system; (iii) establishing with the microprocessor in dependence upon at least the estimate a classification of the input-output data and an identification of a dynamic aspect of the system; (iv) selecting at least one of classification of the input-output data and the identification of the dynamic aspect of the system in dependence upon errors of each with respect to the input-output data; (v) generating a new estimate of the at least one hybrid state of a plurality of hybrid states of the system in dependence upon the selected at least one of classification of the input-output data and the identification of the dynamic aspect of the system; (vi) iterating steps (iii), (iv) and (v) until a predetermined condition is satisfied; (vii) detecting with the microprocessor at least one non-linearity of a plurality of non-linearities; (viii) adjusting the determined parameters from the iterative analysis in dependence upon at least the non-linearity of the plurality of non-linearities; and (ix) determining at least one of a static non-linearity parameter of a plurality of static non-linearity linear dynamic parameters and a linear dynamic parameter of a plurality of linear dynamic parameters.