JISE

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Journal of Information Science and Engineering, Vol. 22 No. 6, pp. 1555-1568

Elman Network with Embedded Memory for System Identification

Adem Kalinli and Seref Sagiroglu^*
Department of Industrial Electronics
Kayseri Vocational High School
Erciyes University
38039, Kayseri, Turkey
^*Department of Computer Engineering
Engineering and Architecture Faculty
Gazi University
06570, Ankara, Turkey

This paper presents a new recurrent neural network (RNN) structure called ENEM for dynamic system identification. ENEM structure is based on Elman network and NARX neural network. In order to show the performance of ENEM for system identification, the results were also compared to the results of Elman network, Jordan network and their modified models. The identification results of linear and nonlinear systems have shown that the proposed ENEM structure is better than the other results of RNN models.

Keywords: Elman network, Jordan network, dynamic system identification, multi-system identification, embedded memory

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