Convergence and steady-state analysis of the normalized least mean fourth algorithm

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...

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Main Author: Zerguine, Azzedine (author)
Other Authors: unknown (author)
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Published: 2007
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author Zerguine, Azzedine
author2 unknown
author2_role author
author_facet Zerguine, Azzedine
unknown
author_role author
dc.creator.none.fl_str_mv Zerguine, Azzedine
unknown
dc.date.none.fl_str_mv 2007-01
2020
dc.identifier.none.fl_str_mv (2007) Convergence and steady-state analysis of the normalized least mean fourth algorithm. Digital Signal Processing, 17 (1). pp. 17-31.
10.1016/j.dsp.2006.01.005
dc.relation.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/1269/
10.1016/j.dsp.2006.01.005
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Electrical
dc.title.none.fl_str_mv Convergence and steady-state analysis of the normalized least mean fourth algorithm
dc.type.none.fl_str_mv Article
PeerReviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description 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 an analysis of the steady-state performance is carried out with a new approach. The latter uses the concept of feedback and bypasses the need for working directly with the weight error covariance matrix. Simulation results obtained in a system identification scenario confirms the theoretical predictions on performance of the NLMF algorithm.
eu_rights_str_mv openAccess
format article
id KFUPM_e80b1d04609ea7580a30dedcabc1d897
identifier_str_mv (2007) Convergence and steady-state analysis of the normalized least mean fourth algorithm. Digital Signal Processing, 17 (1). pp. 17-31.
10.1016/j.dsp.2006.01.005
network_acronym_str KFUPM
network_name_str King Fahd University of Petroleum and Minerals
oai_identifier_str oai::1269
publishDate 2007
repository.mail.fl_str_mv
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spelling Convergence and steady-state analysis of the normalized least mean fourth algorithmZerguine, AzzedineunknownElectricalThe 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 an analysis of the steady-state performance is carried out with a new approach. The latter uses the concept of feedback and bypasses the need for working directly with the weight error covariance matrix. Simulation results obtained in a system identification scenario confirms the theoretical predictions on performance of the NLMF algorithm.2007-012020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article (2007) Convergence and steady-state analysis of the normalized least mean fourth algorithm. Digital Signal Processing, 17 (1). pp. 17-31. 10.1016/j.dsp.2006.01.005https://eprints.kfupm.edu.sa/id/eprint/1269/10.1016/j.dsp.2006.01.005info:eu-repo/semantics/openAccessoai::12692019-11-01T13:26:33Z
spellingShingle Convergence and steady-state analysis of the normalized least mean fourth algorithm
Zerguine, Azzedine
Electrical
status_str publishedVersion
title Convergence and steady-state analysis of the normalized least mean fourth algorithm
title_full Convergence and steady-state analysis of the normalized least mean fourth algorithm
title_fullStr Convergence and steady-state analysis of the normalized least mean fourth algorithm
title_full_unstemmed Convergence and steady-state analysis of the normalized least mean fourth algorithm
title_short Convergence and steady-state analysis of the normalized least mean fourth algorithm
title_sort Convergence and steady-state analysis of the normalized least mean fourth algorithm
topic Electrical