A modified Hopfield model for solving the N-Queens problem

Detalhes bibliográficos
Autor(a) principal: da Silva, I. N.
Data de Publicação: 2000
Outros Autores: de Souza, A. N., Bordon, M. E.
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/IJCNN.2000.859446
http://hdl.handle.net/11449/8890
Resumo: A neural network model for solving the N-Queens problem is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points. The network is shown to be completely stable and globally convergent to the solutions of the N-Queens problem. Simulation results are presented to validate the proposed approach.
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spelling A modified Hopfield model for solving the N-Queens problemA neural network model for solving the N-Queens problem is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points. The network is shown to be completely stable and globally convergent to the solutions of the N-Queens problem. Simulation results are presented to validate the proposed approach.Univ São Paulo, UNESP, FE DEE, Sch Engn,Dept Elect Engn, Bauru, SP, BrazilUniv São Paulo, UNESP, FE DEE, Sch Engn,Dept Elect Engn, Bauru, SP, BrazilInstitute of Electrical and Electronics Engineers (IEEE), Computer SocUniversidade Estadual Paulista (Unesp)da Silva, I. N.de Souza, A. N.Bordon, M. E.2014-05-20T13:27:12Z2014-05-20T13:27:12Z2000-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject509-514http://dx.doi.org/10.1109/IJCNN.2000.859446Ijcnn 2000: Proceedings of the IEEE-inns-enns International Joint Conference on Neural Networks, Vol Vi. Los Alamitos: IEEE Computer Soc, p. 509-514, 2000.1098-7576http://hdl.handle.net/11449/889010.1109/IJCNN.2000.859446WOS:000089240600083821277596049468655898388442982320000-0001-8510-8245Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIjcnn 2000: Proceedings of the IEEE-inns-enns International Joint Conference on Neural Networks, Vol Viinfo:eu-repo/semantics/openAccess2021-10-22T20:56:24Zoai:repositorio.unesp.br:11449/8890Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-22T20:56:24Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A modified Hopfield model for solving the N-Queens problem
title A modified Hopfield model for solving the N-Queens problem
spellingShingle A modified Hopfield model for solving the N-Queens problem
da Silva, I. N.
title_short A modified Hopfield model for solving the N-Queens problem
title_full A modified Hopfield model for solving the N-Queens problem
title_fullStr A modified Hopfield model for solving the N-Queens problem
title_full_unstemmed A modified Hopfield model for solving the N-Queens problem
title_sort A modified Hopfield model for solving the N-Queens problem
author da Silva, I. N.
author_facet da Silva, I. N.
de Souza, A. N.
Bordon, M. E.
author_role author
author2 de Souza, A. N.
Bordon, M. E.
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv da Silva, I. N.
de Souza, A. N.
Bordon, M. E.
description A neural network model for solving the N-Queens problem is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points. The network is shown to be completely stable and globally convergent to the solutions of the N-Queens problem. Simulation results are presented to validate the proposed approach.
publishDate 2000
dc.date.none.fl_str_mv 2000-01-01
2014-05-20T13:27:12Z
2014-05-20T13:27:12Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/IJCNN.2000.859446
Ijcnn 2000: Proceedings of the IEEE-inns-enns International Joint Conference on Neural Networks, Vol Vi. Los Alamitos: IEEE Computer Soc, p. 509-514, 2000.
1098-7576
http://hdl.handle.net/11449/8890
10.1109/IJCNN.2000.859446
WOS:000089240600083
8212775960494686
5589838844298232
0000-0001-8510-8245
url http://dx.doi.org/10.1109/IJCNN.2000.859446
http://hdl.handle.net/11449/8890
identifier_str_mv Ijcnn 2000: Proceedings of the IEEE-inns-enns International Joint Conference on Neural Networks, Vol Vi. Los Alamitos: IEEE Computer Soc, p. 509-514, 2000.
1098-7576
10.1109/IJCNN.2000.859446
WOS:000089240600083
8212775960494686
5589838844298232
0000-0001-8510-8245
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Ijcnn 2000: Proceedings of the IEEE-inns-enns International Joint Conference on Neural Networks, Vol Vi
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 509-514
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers (IEEE), Computer Soc
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers (IEEE), Computer Soc
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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