On the Convergence Analysis of the MINLIP Estimator*

This paper discusses convergence properties of the recently introduced MINimal LIPschitz (MINLIP) estimator for the identification of a monotone Wiener model from noiseless input-output measurements. This estimator is entirely build around the notion of complexity control, making the approach conceptual quite different from traditional identification schemes based on least squares, prediction error methods, maximum likelihood or numerical projections. Sufficient conditions from which the result follows are given in terms of ‘rotational complete inputs', a generalization of the notion of Persistency of Excitation. Finally, we will extend results towards dynamical systems and give examples where this phenomenon occurs.