A time-varying normalized mixed-norm LMS-LMF algorithm

Azzedine Zerguine*

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

7 Scopus citations


The normalized least mean square (NLMS) algorithm is known to result in a faster convergence than the least mean square (LMS) algorithm but at the expense of a larger steady-state error. A time-varying normalized mixed-norm LMS-least mean fourth (LMF) algorithm is presented in this work to preserve the fast convergence of the NLMS algorithm while resulting in a lower steady-state error. The simulation results show that a substantial improvement, in both convergence time and steady state error, can be obtained with this mixed-norm algorithm.

Original languageEnglish
Article number7072073
JournalEuropean Signal Processing Conference
StatePublished - 27 Mar 2002

Bibliographical note

Publisher Copyright:
© 2002 EUSIPCO.

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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