After adding a new hidden neuron, a network simulation is performed in each iteration step;  the input vector with the greatest network’s MSE is found; and Gaussian RBF (radbas) neuron is  added to the hidden layer with weights corresponding to this vector and with constant bias; the linear  layer weights and biases (purelin) are redesignated to minimize the network’s MSE.