Frequency domain analysis of tracking and noise performance of adaptive algorithms

In this paper, an analysis of the tracking and noise performance of several adaptive algorithms is carried out for the case of model structures with fixed pole positions. Such structures have previously been proposed as an efficient generalization of the common FIR model structure. The focus of this work is to analyze the associated tradeoff between noise sensitivity and tracking ability in the frequency domain by illustrating how it is influenced by such things as input and noise spectral densities, step size, and, in particular, the choice of the fixed pole locations. The latter influence is not described by preexisting analysis but is shown here to be amenable to attack by a particular class of orthonormal bases