Dynamic System Identification using Recurrent Radial Basis Function Network

This paper presents a local neural network structure called spatiotemporally local network, by combining the radial basis function network (RBFN) and the local recurrent networks. Three local structures are proposed and the algorithms are compared for nonlinear dynamic system identification. System dynamics can be fully modeled with the fast learning of the proposed neural network structure.