Wavelet-based adaptive robust M-estimator for nonlinear system identification

A wavelet-based robust M-estimation method for the identification of nonlin ear systems is proposed. Because it is not based on the assumption that the re is the class of error distribution, it takes a flexible, nonparametric a pproach and has the advantage of directly estimating the error distribution from the data, This M-estimator is optimal over any error distribution in the sense of maximum likelihood estimation. A Monte-Carlo study on a nonlin ear chemical engineering example was used to compare the results with vario us previously utilized methods.