The logic of neural networks

This paper establishes the equivalence between multilayer feedforward networks and linear combinations of Lukasiewicz propositions. In this sense, multilayer forward networks have a logic interpretation, which should permit to apply logical techniques in the neural networks framework.

Detalles Bibliográficos
Autores: Castro Peña, Juan Luis, Trillas i Gay, Enric
Tipo de recurso: artículo
Fecha de publicación:1998
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2099/3501
Acceso en línea:https://hdl.handle.net/2099/3501
Access Level:acceso abierto
Palabra clave:Feedforward networks
Lukasiewicz logic
Universal aproximators
Squashing functions
Lògica matemàtica
Xarxes neuronals (Informàtica)
Classificació AMS::03 Mathematical logic and foundations::03B General logic
Descripción
Sumario:This paper establishes the equivalence between multilayer feedforward networks and linear combinations of Lukasiewicz propositions. In this sense, multilayer forward networks have a logic interpretation, which should permit to apply logical techniques in the neural networks framework.