Scheduled System Maintenance:
On May 6th, single article purchases and IEEE account management will be unavailable from 8:00 AM - 5:00 PM ET (12:00 - 21:00 UTC). We apologize for the inconvenience.
By Topic

Analysis of an LMS algorithm for unbiased impulse response estimation

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

2 Author(s)
So, H.C. ; Dept. of Comput. Eng. & Inf. Technol., City Univ. of Hong Kong, China ; Chan, Y.T.

In this correspondence, a least mean squares (LMS)-based algorithm is devised for unbiased system identification in the presence of white input and output noise, assuming that the ratio of the noise powers is known. The proposed approach aims to minimize the mean square value of the equation-error function under a constant-norm constraint and is equivalent to minimizing a modified mean square error (MSE) function. An analysis of the algorithm shows that the estimates will converge to the true values in the mean sense. The variances of the parameter estimates are also available. Computer simulations are included to corroborate the theoretical development and to evaluate the impulse response estimation performance of the LMS algorithm under different conditions.

Published in:

Signal Processing, IEEE Transactions on  (Volume:51 ,  Issue: 7 )