Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization

Stop-and-go decision-directed (S&G-DD) equalization is the most primitive blind equalization (BE) method for the cancelling of intersymbol-interference in data communication systems. Recently, this scheme has been applied to complex-valued multilayer feedforward neural network, giving robust res...

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Main Author: Abrar, Shafayat (author)
Other Authors: Zerguine, A. (author), Bettayeb, M. (author), unknown (author)
Format: article
Published: 2002
Subjects:
Online Access:https://eprints.kfupm.edu.sa/id/eprint/14125/1/14125_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14125/2/14125_2.doc
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author Abrar, Shafayat
author2 Zerguine, A.
Bettayeb, M.
unknown
author2_role author
author
author
author_facet Abrar, Shafayat
Zerguine, A.
Bettayeb, M.
unknown
author_role author
dc.creator.none.fl_str_mv Abrar, Shafayat
Zerguine, A.
Bettayeb, M.
unknown
dc.date.none.fl_str_mv 2002-11
2020
dc.format.none.fl_str_mv application/pdf
application/msword
dc.identifier.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/14125/1/14125_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14125/2/14125_2.doc
(2002) Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization. Neural Networks, IEEE Transactions on, 13.
dc.language.none.fl_str_mv en
en
dc.publisher.none.fl_str_mv IEEE
dc.relation.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/14125/
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Computer
dc.title.none.fl_str_mv Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization
dc.type.none.fl_str_mv Article
PeerReviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description Stop-and-go decision-directed (S&G-DD) equalization is the most primitive blind equalization (BE) method for the cancelling of intersymbol-interference in data communication systems. Recently, this scheme has been applied to complex-valued multilayer feedforward neural network, giving robust results with a lower mean-square error at the expense of slow convergence. To overcome this problem, in this work, a fast converging recursive least squares (RLS)-based complex-valued backpropagation learning algorithm is derived for S&G-DD blind equalization. Simulation results show the effectiveness of the proposed algorithm in terms of initial convergence.
eu_rights_str_mv openAccess
format article
id KFUPM_64e16f2777caf129057f3816b4be1165
identifier_str_mv (2002) Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization. Neural Networks, IEEE Transactions on, 13.
language_invalid_str_mv en
network_acronym_str KFUPM
network_name_str King Fahd University of Petroleum and Minerals
oai_identifier_str oai::14125
publishDate 2002
publisher.none.fl_str_mv IEEE
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalizationAbrar, ShafayatZerguine, A.Bettayeb, M.unknownComputerStop-and-go decision-directed (S&G-DD) equalization is the most primitive blind equalization (BE) method for the cancelling of intersymbol-interference in data communication systems. Recently, this scheme has been applied to complex-valued multilayer feedforward neural network, giving robust results with a lower mean-square error at the expense of slow convergence. To overcome this problem, in this work, a fast converging recursive least squares (RLS)-based complex-valued backpropagation learning algorithm is derived for S&G-DD blind equalization. Simulation results show the effectiveness of the proposed algorithm in terms of initial convergence.IEEE2002-112020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/mswordhttps://eprints.kfupm.edu.sa/id/eprint/14125/1/14125_1.pdfhttps://eprints.kfupm.edu.sa/id/eprint/14125/2/14125_2.doc (2002) Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization. Neural Networks, IEEE Transactions on, 13. enenhttps://eprints.kfupm.edu.sa/id/eprint/14125/info:eu-repo/semantics/openAccessoai::141252019-11-01T14:04:18Z
spellingShingle Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization
Abrar, Shafayat
Computer
status_str publishedVersion
title Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization
title_full Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization
title_fullStr Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization
title_full_unstemmed Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization
title_short Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization
title_sort Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization
topic Computer
url https://eprints.kfupm.edu.sa/id/eprint/14125/1/14125_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14125/2/14125_2.doc