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...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | |
| التنسيق: | article |
| منشور في: |
2007
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://eprints.kfupm.edu.sa/id/eprint/590/1/Microsoft_Word_-_Document4.pdf |
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| _version_ | 1864513388845989888 |
|---|---|
| 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.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/590/1/Microsoft_Word_-_Document4.pdf (2007) Convergence and steady-state analysis of the normalized least mean fourth algorithm. Digital Signal Processing, 17 (1). pp. 17-31. ISSN 1051-2004 10.1016/j.dsp.2006.01.005 |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | Academic Press, Inc. |
| dc.relation.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/590/ 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_dc4548c901ec349ea54c47927aa28ad3 |
| identifier_str_mv | (2007) Convergence and steady-state analysis of the normalized least mean fourth algorithm. Digital Signal Processing, 17 (1). pp. 17-31. ISSN 1051-2004 10.1016/j.dsp.2006.01.005 |
| language_invalid_str_mv | en |
| network_acronym_str | KFUPM |
| network_name_str | King Fahd University of Petroleum and Minerals |
| oai_identifier_str | oai::590 |
| publishDate | 2007 |
| publisher.none.fl_str_mv | Academic Press, Inc. |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| 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.Academic Press, Inc.2007-012020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://eprints.kfupm.edu.sa/id/eprint/590/1/Microsoft_Word_-_Document4.pdf (2007) Convergence and steady-state analysis of the normalized least mean fourth algorithm. Digital Signal Processing, 17 (1). pp. 17-31. ISSN 1051-2004 10.1016/j.dsp.2006.01.005enhttps://eprints.kfupm.edu.sa/id/eprint/590/10.1016/j.dsp.2006.01.005info:eu-repo/semantics/openAccessoai::5902019-11-01T13:24:35Z |
| 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 |
| url | https://eprints.kfupm.edu.sa/id/eprint/590/1/Microsoft_Word_-_Document4.pdf |