Artificial neural network-based algorithm for ARMA model order estimation

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Abstract

This paper presents a new algorithm for the determination of the Autoregressive Moving Average (ARMA) model order based on Artificial Neural Network (ANN). The basic idea is to apply ANN to a special matrix constructed from the Minimum Eginevalue (MEV) criterion. The MEV criterion is based on a covariance matrix derived from the observed output data only. The input signal is unobservable. The proposed algorithm is based on training the MEV covariance matrix dataset using the back-propagation technique. Our goal is to develop a system based on ANN; hence, the model order can be selected automatically without the need of prior knowledge about the model or any human intervention. Examples are given to illustrate the significant improvement results. © 2010 Springer-Verlag Berlin Heidelberg.

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Al-Qawasmi, K. E., Al-Smadi, A. M., & Al-Hamami, A. (2010). Artificial neural network-based algorithm for ARMA model order estimation. In Communications in Computer and Information Science (Vol. 88 CCIS, pp. 184–192). https://doi.org/10.1007/978-3-642-14306-9_19

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