Fast recursive basis function estimators for identification of time-varying processes

Abstract

When system parameters vary rapidly with time, the weighted least squares filters are not capable of following the changes satisfactorily; some more elaborate estimation schemes, based on the method of basis functions, have to be used instead. The basis function estimators have increased tracking capabilities but are computationally very demanding. The paper introduces a new class of adaptive filters, based on the concept of postfiltering, which have improved parameter tracking capabilities that are typical of the basis function algorithms but, at the same time, have pretty low computational requirements, which is typical of the weighted least squares algorithms.