Combined Regressor Methods and Adaptive IIR Filtering

Abstract

An open issue in adaptive infinite-impulse response (IIR) filtering is that of convergence to a global minimum in the presence of observation noise when the system is insufficiently modeled . It is well known , that algorithms based on equation error (EE) formulation contain a single minimum that may be biased whereas, algorithms based on output error (OE) ensure the existence of an unbiased global minimum in presence of local minima. Recently, there have been several attempts to combine these formulations in order to ensure the existence and uniqueness of an unbiased minimum. Works presented here, EEOE and modified EEOE (MEEOE), are such attempts in the context of system identification. We will show, analytically and through simulations, the convergence properties of the MEEOE approach, in the context of system identification.