Journal ArticleDOI
A variable step size LMS algorithm
Raymond H. Kwong,E.W. Johnston +1 more
TLDR
A least-mean-square adaptive filter with a variable step size, allowing the adaptive filter to track changes in the system as well as produce a small steady state error, is introduced.Abstract:
A least-mean-square (LMS) adaptive filter with a variable step size is introduced. The step size increases or decreases as the mean-square error increases or decreases, allowing the adaptive filter to track changes in the system as well as produce a small steady state error. The convergence and steady-state behavior of the algorithm are analyzed. The results reduce to well-known results when specialized to the constant-step-size case. Simulation results are presented to support the analysis and to compare the performance of the algorithm with the usual LMS algorithm and another variable-step-size algorithm. They show that its performance compares favorably with these existing algorithms. >read more
Citations
More filters
Journal ArticleDOI
Application of antenna arrays to mobile communications. II. Beam-forming and direction-of-arrival considerations
TL;DR: This paper provides a comprehensive and detailed treatment of different beam-forming schemes, adaptive algorithms to adjust the required weighting on antennas, direction-of-arrival estimation methods-including their performance comparison-and effects of errors on the performance of an array system, as well as schemes to alleviate them.
Journal ArticleDOI
A robust variable step-size LMS-type algorithm: analysis and simulations
Tyseer Aboulnasr,K. Mayyas +1 more
TL;DR: A robust variable step-size LMS-type algorithm providing fast convergence at early stages of adaptation while ensuring small final misadjustment is presented, providing performance equivalent to that of the regular LMS algorithm.
Journal ArticleDOI
Variable step-size NLMS and affine projection algorithms
TL;DR: This letter proposes two new variable step-size algorithms for normalized least mean square and affine projection that lead to faster convergence rate and lower misadjustment error.
Journal ArticleDOI
Mean-square performance of a convex combination of two adaptive filters
TL;DR: This paper studies the mean-square performance of a convex combination of two transversal filters and shows how the universality of the scheme can be exploited to design filters with improved tracking performance.
Journal ArticleDOI
A Nonparametric VSS NLMS Algorithm
TL;DR: A new nonparametric VSS-NLMS is proposed that is easy to control and gives good performances in the context of acoustic echo cancellation.
References
More filters
Journal ArticleDOI
Adaptive noise cancelling: Principles and applications
Bernard Widrow,J.R. Glover,John M. McCool,J. Kaunitz,C.S. Williams,R.H. Hearn,James R. Zeidler,Jr. Eugene Dong,R.C. Goodlin +8 more
TL;DR: It is shown that in treating periodic interference the adaptive noise canceller acts as a notch filter with narrow bandwidth, infinite null, and the capability of tracking the exact frequency of the interference; in this case the canceller behaves as a linear, time-invariant system, with the adaptive filter converging on a dynamic rather than a static solution.
Book ChapterDOI
Stationary and nonstationary learning characteristics of the LMS adaptive filter
TL;DR: It is shown that for stationary inputs the LMS adaptive algorithm, based on the method of steepest descent, approaches the theoretical limit of efficiency in terms of misadjustment and speed of adaptation when the eigenvalues of the input correlation matrix are equal or close in value.
Journal ArticleDOI
A variable step (VS) adaptive filter algorithm
R. Harris,D. Chabries,F. Bishop +2 more
TL;DR: It is shown that an upper bound for the convergence time is the classical mean-square-error time constant, and examples are given to demonstrate that for broad signal classes the convergenceTime is reduced by a factor of up to 50 in noise canceller applications for the proper selection of variable step parameters.
Journal ArticleDOI
Convergence analysis of LMS filters with uncorrelated Gaussian data
Arie Feuer,E. Weinstein +1 more
TL;DR: It is found that the adaptive coefficient μ, which controls the rate of convergence of the algorithm, must be restricted to an interval significantly smaller than the domain commonly stated in the literature.
Journal ArticleDOI
Silencing echoes on the telephone network
M.M. Sondhi,D.A. Berkley +1 more
TL;DR: Echo cancellers may be applied to the network in a number of ways and the development of a VLSI canceller chip promises inexpensive implementation of these applications.