A Radial Basis Function Network
A Radial Basis Function Network (RBFN) is a type of artificial neural network that uses radial basis functions as activation functions.
Areas of application
- Pattern recognition
- Time series prediction
- System control
- Medical imaging
- Image processing
- Speech and handwriting recognition
- Data mining
- Climate modeling
Example
For example, an RBFN could be used to model the relationship between temperature and pressure in a gas turbine engine. The radial basis functions could be used to represent the temperature and pressure variables in a high-dimensional space, allowing the network to learn the underlying patterns and relationships in the data.