Multi/infinite dimensional neural networks, multi/infinite dimensional logic theory.
Int J Neural Syst
; 15(3): 223-35, 2005 Jun.
Article
en En
| MEDLINE
| ID: mdl-16013092
ABSTRACT
A mathematical model of an arbitrary multi-dimensional neural network is developed and a convergence theorem for an arbitrary multi-dimensional neural network represented by a fully symmetric tensor is stated and proved. The input and output signal states of a multi-dimensional neural network/logic gate are related through an energy function, defined over the fully symmetric tensor (representing the connection structure of a multi-dimensional neural network). The inputs and outputs are related such that the minimum/maximum energy states correspond to the output states of the logic gate/neural network realizing a logic function. Similarly, a logic circuit consisting of the interconnection of logic gates, represented by a block symmetric tensor, is associated with a quadratic/higher degree energy function. Infinite dimensional logic theory is discussed through the utilization of infinite dimension/order tensors.
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Base de datos:
MEDLINE
Asunto principal:
Redes Neurales de la Computación
/
Lógica
Tipo de estudio:
Risk_factors_studies
Idioma:
En
Revista:
Int J Neural Syst
Asunto de la revista:
ENGENHARIA BIOMEDICA
/
INFORMATICA MEDICA
Año:
2005
Tipo del documento:
Article