An alternative proof of the universality of the CNN-UM and its practical applications

Giovanni Egidio Pazienza, Xavier Vilasís-Cardona, Riccardo Poli

Producción científica: Capítulo del libroContribución a congreso/conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

In this paper we give a proof of the universality of the Cellular Neural Network - Universal Machine (CNN-UM) alternative to those presented so far. On the one hand, this allows to find a general structure for CNN-UM programs; on the other hand, it helps to formally demonstrate that machine learning techniques can be used to find CNN-UM programs automatically. Finally, we report on two experiments in which our system is able to propose new efficient solutions.

Idioma originalInglés
Título de la publicación alojada2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures
Páginas34-39
Número de páginas6
DOI
EstadoPublicada - 2008
Evento2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures - Santiago de Compostela, Espana
Duración: 14 jul 200816 jul 2008

Serie de la publicación

NombreProceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications

Conferencia

Conferencia2008 11th International Workshop on Cellular Neural Networks and their Applications, CNNA 2008, Cellular Nano-scale Architectures
País/TerritorioEspana
CiudadSantiago de Compostela
Período14/07/0816/07/08

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