Adaptive system identification using robust LMS/F algorithm

Guan Gui, Wei Peng, Fumiyuki Adachi

Research output: Contribution to journalArticlepeer-review

35 Citations (Scopus)

Abstract

Adaptive system identification (ASI) problems have attracted both academic and industrial attentions for a long time. As one of the classical approaches for ASI, performance of least mean square (LMS) is unstable in low signal-to-noise ratio (SNR) region. On the contrary, least mean fourth (LMF) algorithm is difficult to implement in practical system because of its high computational complexity in high SNR region, and hence it is usually neglected by researchers. In this paper, we propose an effective approach to identify unknown system adaptively by using combined LMS and LMF algorithms in different SNR regions. Experiment-based parameter selection is established to optimize the performance as well as to keep the low computational complexity.

Original languageEnglish
Pages (from-to)2956-2963
Number of pages8
JournalInternational Journal of Communication Systems
Volume27
Issue number11
DOIs
Publication statusPublished - 2014 Nov 1

Keywords

  • Adaptive system identification (ASI)
  • LMF
  • LMS
  • LMS/F

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Adaptive system identification using robust LMS/F algorithm'. Together they form a unique fingerprint.

Cite this