Generic method for solving partial differential equations through the design of problem-specific Cellular Neural Networks - Archive ouverte HAL
Pré-Publication, Document De Travail Année : 2007

Generic method for solving partial differential equations through the design of problem-specific Cellular Neural Networks

Hervé Frezza-Buet

Résumé

This paper presents an original and generic numerical method for solving partial differential equations. A new mathematical and systematic method stemming from the local very nature of any differential problem is proposed: a custom tailored continuous automaton is purposely derived from any given differential problem so that its steady state yields the solution in a quantitatively correct way. The combined use of formal computing and continuous automata thus offers the unique possibility to completely automate the process from formal problem specification to its numerical solution.
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Dates et versions

hal-00107064 , version 1 (17-10-2006)
hal-00107064 , version 2 (18-10-2006)
hal-00107064 , version 3 (13-11-2006)
hal-00107064 , version 4 (26-01-2007)
hal-00107064 , version 5 (24-05-2007)
hal-00107064 , version 6 (05-06-2009)
hal-00107064 , version 7 (31-08-2009)
hal-00107064 , version 8 (29-01-2010)

Identifiants

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Nicolas Fressengeas, Hervé Frezza-Buet. Generic method for solving partial differential equations through the design of problem-specific Cellular Neural Networks. 2007. ⟨hal-00107064v5⟩
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