Title: Back-propagation algorithm to estimate the parameters of auto-regressive exogenous model

Authors: Tianyang Xu; Jing Chen; Yingjiao Rong

Addresses: School of Science, Jiangnan University, Wuxi, China ' School of Science, Jiangnan University, Wuxi, China; Science and Technology on Near-Surface Detection Laboratory, Wuxi, China ' Science and Technology on Near-Surface Detection Laboratory, Wuxi, China

Abstract: This paper proposes a back-propagation (BP) algorithm to estimate the parameters of auto-regressive exogenous (ARX) models. By using the SAG method, the proposed algorithm identifies the weights/parameters of the neutral network constructed for the ARX model. Furthermore, in order to decrease the oscillation phenomenon in the SAG algorithm, two modified SAG algorithms are developed. A simulation experiment is presented to verify the effectiveness of the proposed methods.

Keywords: system identification; SAG; sliding data window; weighted; BP neural network.

DOI: 10.1504/IJMIC.2021.121830

International Journal of Modelling, Identification and Control, 2021 Vol.37 No.3/4, pp.224 - 231

Received: 17 Sep 2020
Accepted: 17 Jan 2021
Published online: 07 Apr 2022 *

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