A family of consistent Steiglitz-McBride algorithms for IIR adaptive filtering

Abstract

In this paper is proposed a family of algorithms based on the Steiglitz-McBride (SM) method for IIR adaptive filtering. The main feature of the algorithms is that the resulting estimates are consistent. The conceptual similarities between the SM method and the equation error (EE) method are explored in order to derive some properties of the new algorithms. In particular, some basic properties of the proposed algorithms are analysed, namely the stationary points and local convergence. The general performance of the new algorithms are verified through some simulations of system identification application.