By Topic

Nonlinear quantization effects in the LMS and block LMS adaptive algorithms-a comparison

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

1 Author(s)
Bershad, N.J. ; Dept. of Electr. Eng., California Univ., Irvine, CA, USA

Analog implementations of the LMS (least-mean squares) and block LMS (BLMS) adaptive filtering algorithms have been shown to be equivalent with respect to adaptation speed and steady-state misadjustment errors. However, the BLMS algorithm offers significant reductions in computational speed due to block processing. Digital implementations of the two algorithms are compared with respect to finite word effects. The algorithm stalling phenomena is studied using Gaussian data and conditional expectation arguments. It is shown that the BLMS algorithm requires 1/2(log2L-K) fewer bits for the same stalling behavior (L=block length and K lies between 0.2 and 1, depending on the precise definition of algorithm stalling). The LMS algorithm requires log2L fewer bits than BLMS for the same level of saturation behavior (transient response) at algorithm initialization. Hence, overall the LMS algorithm requires 1/2(log2L+K) fewer bits than the BLMS algorithm for the same saturation and stalling effects

Published in:

Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on

Date of Conference:

11-14 Apr 1988