Neural Network Implementation for Function Approximation

The primary functions utilized for implementing function approximation via neural networks are: NEWRB - designs a radial basis function neural network, and SIM - performs simulation of the radial basis function network. The NEWRB function automatically determines the optimal number of neurons and centers while adjusting weights through least-squares optimization. The SIM function executes network inference by calculating radial basis function activations and weighted summations.