Variable weight mixed-norm LMS-LMF adaptive algorithm

Tyseer Aboulnasr, Azzedine Zerguine

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

20 Scopus citations

Abstract

In this paper, we propose a new mixed norm LMS-LMF adaptive algorithm. The algorithm minimizes an objective function defined as a weighted sum of the least mean fourth (LMF) and least mean square (LMS) cost functions. The weighting factor is time varying and adapts itself so as to emphasize one cost function over the other based on proximity to the optimum. Improved convergence is illustrated by examples. Bounds on the step size to ensure mean convergence are also derived.

Original languageEnglish
Title of host publicationConference Record of the 33rd Asilomar Conference on Signals, Systems, and Computers
EditorsMichael B. Matthews
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages791-794
Number of pages4
ISBN (Electronic)0780357000, 9780780357006
DOIs
StatePublished - 1999

Publication series

NameConference Record of the 33rd Asilomar Conference on Signals, Systems, and Computers
Volume1

Bibliographical note

Publisher Copyright:
© 1999 IEEE.

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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