  A generalization of the dynamic regressor extension and mixing procedure is
proposed, which, unlike the original procedure, first, guarantees a reduction
of the unknown parameter identification error if the requirement of regressor
semi-finite excitation is met, and second, it ensures exponential convergence
of the regression function (regressand) tracking error to zero when the
regressor is semi-persistently exciting with a rank one or higher.
