Title :
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
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;
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
DOI :
10.1109/ASSPCC.2000.882484
