A Modified elman network with memory units for system identification

Abstract

In this paper we propose a modified Elman network structure called memory Elman neural network. The idea of this new architecture is based on adding memory units to the neurons of the classic Elman network. These memory units are trainable temporal elements that make the output history-sensitive. By virtue of this capacity, this new architecture can take into account the past information of the neurons and use them in order to accomplish the task of the network. In order to show the performance of this new network, some dynamical systems are used for identification and results are compared with the conventional Elman network