« Réseau de neurones à fonction de base radiale » : différence entre les versions
m (Remplacement de texte — « DeepAI.org ] » par « DeepAI.org ] Catégorie:DeepAI.org ») |
Aucun résumé des modifications |
||
| Ligne 9 : | Ligne 9 : | ||
== Anglais == | == Anglais == | ||
''' Radial basis function network ''' | ''' Radial basis function network ''' | ||
'''RBFNs''' | |||
In the field of mathematical modeling, a radial basis function network is an artificial neural network that uses radial basis functions as activation functions. The output of the network is a linear combination of radial basis functions of the inputs and neuron parameters. Radial basis function networks have many uses, including function approximation, time series prediction, classification, and system control. They were first formulated in a 1988 paper by Broomhead and Lowe, both researchers at the Royal Signals and Radar Establishment. | In the field of mathematical modeling, a radial basis function network is an artificial neural network that uses radial basis functions as activation functions. The output of the network is a linear combination of radial basis functions of the inputs and neuron parameters. Radial basis function networks have many uses, including function approximation, time series prediction, classification, and system control. They were first formulated in a 1988 paper by Broomhead and Lowe, both researchers at the Royal Signals and Radar Establishment. | ||
<small> | <small> | ||
[https://en.wikipedia.org/wiki/Glossary_of_artificial_intelligence Source : Wikipedia] | [https://en.wikipedia.org/wiki/Glossary_of_artificial_intelligence Source : Wikipedia] | ||
Version du 7 septembre 2021 à 15:47
en construction
Définition
Français
Anglais
Radial basis function network
RBFNs
In the field of mathematical modeling, a radial basis function network is an artificial neural network that uses radial basis functions as activation functions. The output of the network is a linear combination of radial basis functions of the inputs and neuron parameters. Radial basis function networks have many uses, including function approximation, time series prediction, classification, and system control. They were first formulated in a 1988 paper by Broomhead and Lowe, both researchers at the Royal Signals and Radar Establishment.
Contributeurs: Jean Benoît Morel, wiki
