A unifying view of error nonlinearities in LMS adaptation

Tareq Y. Al-Naffouri, Azzedine Zerguine, Maamar Bettayeb

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

This paper presents a unifying view of various error nonlinearities that are used in least mean square (LMS) adaptation such as the least mean fourth (LMF) algorithm and its family and the least-mean mixed-norm algorithm. Specifically, it is shown that the LMS algorithm and its error-modified variants are approximations of two previously developed optimum nonlinearities which are expressed in terms of the additive noise probability density function (PDF). This is demonstrated through an approximation of the optimum nonlinearities by expanding the noise PDF in a Gram-Charlier series. Thus a link is established between intuitively proposed and theoretically justified variants of the LMS algorithm. The approximation has also a practical advantage in that it provides a trade-off between simplicity and more accurate realization of the optimum nonlinearities.

Original languageEnglish (US)
Title of host publicationProceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1697-1700
Number of pages4
Volume3
ISBN (Print)0780344286, 9780780344280
DOIs
StatePublished - 1998
Externally publishedYes
Event1998 23rd IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998 - Seattle, WA, United States
Duration: May 12 1998May 15 1998

Other

Other1998 23rd IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998
CountryUnited States
CitySeattle, WA
Period05/12/9805/15/98

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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