A functional network modeling approach for function series expansion

In this paper, a novel function series expansion method based on functional network model is proposed, and a functional network model for functions in several variables series expansion and learning algorithm are given, the learning of parameters of the functional networks is carried out by the solving linear equations. The simulation results show that the proposed approach is more efficient and feasible in function series expansion. By this algorithm, we only need the sample space of the original functions. So this algorithm has the value of application in industries.