Weights direct determination of a spline neural network

Based on spline approximation theory and neural networks, a spline neural network is constructed, where the hidden-layer neurons are activated by a group of spline functions. Based on the standard error back-propagation (BP) method, the neural-weights updating formula is derived. More importantly, a pseudo-inverse based method is then proposed, which could directly determine the network weights without iterative training. Computer simulation results show that the one-step weights-determination method could be more effective than the standard BP iterative-training method.