Adaptive IIR filtering for noisy input-output systems

Abstract

This paper is concerned with adaptive IIR filtering for linear systems with noisy input and output measurements. A new and numerically efficient procedure for estimating the variances of the white input and output noises is established so that the adaptive IIR filter based on the bias-eliminated least-squares algorithm can be efficiently implemented. This new adaptive IIR filter can achieve a substantial reduction in computational effort, and can retain almost the same parameter estimation accuracy. Numerical results that illustrate the attractive properties of the new adaptive FIR filter are presented.