Convergence behavior of the normalized least mean fourth algorithm

A. Zerguine*

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

33 Scopus citations

Abstract

The normalized least mean fourth (NLMF) algorithm is presented in this work and shown to have potentially faster convergence. Unlike the LMF algorithm, the convergence behavior of the NLMF algorithm is independent of the input data correlation statistics. Sufficient conditions for the NLMF algorithm convergence in the mean are obtained and the analysis of the steady-state performance is carried out using the feedback approach. Simulation results confirm the performance of the NLMF algorithm.

Original languageEnglish
Pages (from-to)275-278
Number of pages4
JournalConference Record of the Asilomar Conference on Signals, Systems and Computers
Volume1
StatePublished - 2000

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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