Using Radial Basis Function Networks for Function Approximation and Classification
Figure 1
Architecture of the RBF network. The input, hidden, and output layers have , , and neurons, respectively. corresponds to the bias in the output layer, while ’s denote the nonlinearity at the hidden nodes.
