Java Radial Basis Function Neural Network

The Radial Basis Function neural network contains a hidden layer based on radial basis functions (RBF). A radial basis function is a function that peaks in the center and rapidly falls off in each direction along an axis. One of the most common examples of a RBF is the Gaussian function. The hidden layer consists of one or more RBF's. This allows for a complex function to be modeled inside of the hidden layers. RBF neural networks are used for a variety of purposes, such as function approximation and prediction.

The Radial Basis Function Neural Network modeled in the Encog Workbench looks like this: