By Topic

On the "Desired behavior" of adaptive signal processing algorithms

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Farden, D.C. ; University of Rochester, Rochester, New York ; Goding, J., Jr. ; Sayood, K.

Sufficient conditions are presented for establishing "desirable" convergence properties of commonly used adaptive signal processing algorithms which use correlated training data. The family of algoriths considered includes the Widrow LMS algorithm. Desirable properties include, e.g., an asymptotic bound on the mean-square error between the parameter vector trained by the adaptive algorithm and the optimal solution. This asymptotic bound should decrease with decreasing step size. The results contained in this paper illustrate the trade-offs involved in choosing the step size to achieve an acceptable convergence rate as well as an acceptable steady state error. The sufficient conditions include bounded data and easily verified covariance decay rate conditions.

Published in:

Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '79.  (Volume:4 )

Date of Conference:

Apr 1979