Analysis of adaptive filters using normalized signed regressor LMS algorithm

In this paper, adaptive filters using the normalized signed regressor LMS algorithm (NSRA) with Gaussian reference inputs are proposed and analyzed to yield difference equations for theoretically calculating expected convergence of the filters. A simple difference equation for mean squared error (MS...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on signal processing Vol. 47; no. 10; pp. 2710 - 2723
Main Author: Koike, S.
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.10.1999
Institute of Electrical and Electronics Engineers
Subjects:
Adaptive filters
Algorithm design and analysis
Algorithms
Applied sciences
Approximation
Circuits
Convergence
Detection, estimation, filtering, equalization, prediction
Difference equations
Exact sciences and technology
Filtering theory
Gaussian
Gaussian processes
Information, signal and communications theory
Least squares approximation
Mathematical analysis
Regression analysis
Signal and communications theory
Signal, noise
Stability
Steady-state
Telecommunications and information theory
Gaussian process
Circuit design
Computer simulation
Theoretical study
Signal processing
Stability criterion
Adaptive filter
Difference equation
Mean square error
Signal to noise ratio
ISSN:1053-587X
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, adaptive filters using the normalized signed regressor LMS algorithm (NSRA) with Gaussian reference inputs are proposed and analyzed to yield difference equations for theoretically calculating expected convergence of the filters. A simple difference equation for mean squared error (MSE) is derived when the filter input is a white and Gaussian process, whereas approximate difference equations for colored Gaussian inputs are proposed and tested. Stability conditions and residual MSE after convergence are also obtained. Agreement of theoretical results with those of simulation in the experiment with some examples of filter convergence shows sufficient accuracy of the theory and assures the usefulness of the difference equations in estimating filter performances, thus facilitating the design of adaptive filters using the NSRA.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ObjectType-Article-2
ObjectType-Feature-1
ISSN:1053-587X
DOI:10.1109/78.790653