Analytical model for the mean weight behavior of adaptive interpolated-FIR filters using the constrained filtered LMS algorithm

Author

Tobias, Orlando J. ; Seara, Rui

Author_Institution

Dept. of Electr. Eng., Fed. Univ. of Santa Catarina, Florianopolis, Brazil

fYear

2000

fDate

2000

Firstpage

272

Lastpage

277

Abstract

This paper presents an analytical model for the mean weight behavior of adaptive interpolated-FIR filters using the constrained filtered LMS algorithm. The introduction of an interpolating block cascaded with the adaptive sparse filter imposes that the input signal correlation must be considered. It is well known that such correlation is disregarded by the independence theory, which is the base for the analysis of the ordinary LMS algorithm. In addition, the effect of the IFIR topology on the model is accounted using a constrained approach. Experimental results demonstrate the effectiveness of the proposed analytical model as compared to classical analysis

Keywords

FIR filters; adaptive filters; correlation methods; filtering theory; interpolation; least mean squares methods; IFIR topology; adaptive interpolated-FIR filters; adaptive sparse filter; analytical model; constrained filtered LMS algorithm; independence theory; input signal correlation; mean weight behavior; Adaptive filters; Analytical models; Arithmetic; Circuits; Finite impulse response filter; Instruments; Laboratories; Least squares approximation; Signal processing algorithms; Topology;

fLanguage

English

Publisher

ieee

Conference_Titel

Adaptive Systems for Signal Processing, Communications, and Control Symposium 2000. AS-SPCC. The IEEE 2000

Conference_Location

Lake Louise, Alta.

Print_ISBN

0-7803-5800-7

Type

conf

DOI

10.1109/ASSPCC.2000.882484

Filename

882484