Types of recurrent neural networks for non-linear dynamic system modelling

Abstract

Recurrent neural networks are represented as non-linear models of dynamic systems. This kind of neural networks is divided into two groups, which are globally and locally recurrent neural networks. Some types are distinguished among globally recurrent networks. The major approximation properties and features of every distinguished type are emphasized. The represented analysis is useful for choosing the neural network structure a priori (prior to its training or constructing the mathematical model of the nonlinear system).