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dc.contributor.authorMedina Moreno, Jesús
dc.contributor.authorMérida-Casermeiro, Enrique
dc.contributor.authorOjeda Aciego, Manuel
dc.date.accessioned2006-06-13T16:45:05Z
dc.date.available2006-06-13T16:45:05Z
dc.date.issued2005
dc.identifier.issn1134-5632
dc.identifier.urihttp://hdl.handle.net/2099/1832
dc.description.abstractA generalization of the homogenization process needed for the neural im- plementation of multi-adjoint logic programming (a unifying theory to deal with uncertainty, imprecise data or incomplete information) is presented here. The idea is to allow to represent a more general family of adjoint pairs, but maintaining the advantage of the existing implementation recently introduced in [6]. The soundness of the transformation is proved and its complexity is analysed. In addition, the corresponding generalization of the neural-like implementation of the fixed point semantics of multi-adjoint is presented.
dc.language.isoeng
dc.publisherUniversitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica
dc.relation.ispartofMathware & soft computing, 2005, vol. 12, núm. 3
dc.rightsReconeixement-NoComercial-CompartirIgual 3.0 Espanya
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.otherLogic programming
dc.subject.otherNeural implementation
dc.titleA neural implementation of multi-adjoint logic programs via sf-homogenization
dc.typeArticle
dc.subject.lemacInformàtica -- Matemàtica
dc.subject.lemacProgramació lògica
dc.subject.lemacXarxes neuronals (Informàtica)
dc.subject.amsClassificació AMS::68 Computer science::68R Discrete mathematics in relation to computer science
dc.rights.accessOpen Access


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