Frequency domain analysis of tracking and noise performance of adaptive algorithms

Author

Ninness, Brett ; Gomez, Juan Carlos

Author_Institution

Dept. of Electr. & Comput. Eng., Newcastle Univ., NSW, Australia

Volume

46

Issue

5

fYear

1998

fDate

5/1/1998 12:00:00 AM

Firstpage

1314

Lastpage

1332

Abstract

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

Keywords

adaptive filters; frequency-domain analysis; least mean squares methods; noise; pole assignment; recursive estimation; spectral analysis; tracking filters; LMS; adaptive algorithms; fixed pole locations; fixed pole positions; frequency domain analysis; model structures; noise performance; noise sensitivity; noise spectral densities; orthonormal bases; recursive estimation; step size; tracking; tracking ability; Adaptive algorithm; Adaptive filters; Algorithm design and analysis; Convergence; Degradation; Filtering algorithms; Finite impulse response filter; Frequency domain analysis; Least squares approximation; Recursive estimation;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.668794

Filename

668794