Tracking analysis of the ε-NSRLMMN algorithm

Mohammed Mujahid Ulla Faiz*, Azzedine Zerguine

*Corresponding author for this work

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

1 Scopus citations

Abstract

In this work, expressions for the tracking excess-mean-square error (EMSE) and optimum step-size of the ε-normalized sign regressor least mean mixed-norm (NSRLMMN) adaptive algorithm are derived. Finally, extensive simulation results performed are found to corroborate very closely with the theoretical results for correlated Gaussian data.

Original languageEnglish
Title of host publicationConference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012
Pages816-819
Number of pages4
DOIs
StatePublished - 2012

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

Fingerprint

Dive into the research topics of 'Tracking analysis of the ε-NSRLMMN algorithm'. Together they form a unique fingerprint.

Cite this