Preferred Label : Radial Basis Function Networks;
MeSH definition : A three-layer neural network made of an input layer, hidden layer, and output layer.
Radial basis function networks are used for function approximation, interpolation,
classification, and time series prediction.;
Définition CISMeF : 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. (see https://en.wikipedia.org/wiki/Radial_basis_function_network).;
MeSH synonym : RBF Neural Networks; Network, RBF Neural; Neural Network, RBF; RBF Neural Network; Radial Basis Function Neural Networks; RBFNNs; Radial Basis Networks; Network, Radial Basis; Radial Basis Network;
Related MeSH term : Function, Radial Basis; Radial Basis Function;
Origin ID : D000098423;
UMLS CUI : C5940546;
Record concept(s)
- Semantic type(s)
A three-layer neural network made of an input layer, hidden layer, and output layer.
Radial basis function networks are used for function approximation, interpolation,
classification, and time series prediction.
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. (see https://en.wikipedia.org/wiki/Radial_basis_function_network).
