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.
| Autores: | , |
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| 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 |
| 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. |
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