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A neural implementation of multi-adjoint logic programs via sf-homogenization

  • Autores: Jesús Medina Moreno Árbol académico, Enrique Mérida Casermeiro Árbol académico, Manuel Ojeda Aciego Árbol académico
  • Localización: Mathware & soft computing: The Magazine of the European Society for Fuzzy Logic and Technology, ISSN-e 1134-5632, Vol. 12, Nº. 3, 2005, págs. 199-216
  • Idioma: inglés
  • Títulos paralelos:
    • Una implementación neuronal de programas lógicos multi-adjuntos mediante homogeneización sf
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  • Resumen
    • A generalization of the homogenization process needed for the neural implementation 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.


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